Formal Ontology and Information Systems

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Formal Ontology and Information Systems

• Barry Smith
• http//ifomis.de

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• Part I Research in Formal Ontology
• Part II Some Implications for Agent-Based and
  Situated Computing

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Part I

• Institute for Formal Ontology and Medical
  Information Science
• (IFOMIS)
• Faculty of Medicine
• University of Leipzig
• http//ifomis.de

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The Idea

• Computational medical research
• will transform the discipline of medicine
• but only if communication problems can be solved

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Medicine

• desperately needs to find a way
• to enable the huge amounts of data
• resulting from trials by different groups
• to be (f)used together

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How resolve incompatibilities?

• ONTOLOGY the solution of first resort
• (compare kicking a television set)
• But what does ontology mean?
• Current most popular answer a collection of
  terms and definitions satisfying constraints of
  description logic

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Description logic

• a decidable logic
• (thus much weaker than first-order predicate
  logic)
• for manipulating hierarchies of concepts/general
  terms)

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Example The Enterprise Ontology

• A Sale is an agreement between two Legal-Entities
  for the exchange of a Product for a Sale-Price.
• A Strategy is a Plan to Achieve a high-level
  Purpose.
• A Market is all Sales and Potential Sales within
  a scope of interest.

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Harvard Business Review, October 2001

• Trying to engage with too many partners too
  fast is one of the main reasons that so many
  online market makers have foundered. The
  transactions they had viewed as simple and
  routine actually involved many subtle
  distinctions in terminology and meaning

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Example Medical Nomenclature

• Unified Medical Language System (UMLS)
• blood is a tissue
• Systematized Nomenclature of Medicine (SNOMED)
• blood is a fluid

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Example Statements of Accounts

• Company Financial statements may be prepared
  under either the (US) GAAP or the (European) IASC
  standards
• These allocate cost items to different
  categories depending on the laws of the countries
  involved.

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Job

• to develop an algorithm for the automatic
  conversion of income statements and balance
  sheets between the two systems.
• Not even this relatively simple problem has been
  satisfactorily resolved
• why not?

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Example The Gene Ontology (GO)

• hormone GO0005179
• digestive hormone GO0046659
• peptide hormone GO0005180 adrenocorticotrop
  in GO0017043 glycopeptide hormone
  GO0005181 follicle-stimulating hormone
  GO0016913

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as tree

• hormone
• digestive hormone peptide hormone
• adrenocorticotropin
  glycopeptide hormone
• 
  follicle-stimulating hormone

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Problem There exist multiple databases

• genomic
• cellular
• structural
• phenotypic
• and even for each specific type of information,
  e.g. DNA sequence data, there exist several
  databases of different scope and organisation

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What is a gene?

• GDB a gene is a DNA fragment that can be
  transcribed and translated into a protein
• Genbank a gene is a DNA region of biological
  interest with a name and that carries a genetic
  trait or phenotype
• (from Schulze-Kremer)
• GO does not tell us which of these is correct,
  or indeed whether either is correct, and it does
  not tell us how to integrate data from the
  corresponding sources

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Example The Semantic Web

• Vast amount of heterogeneous data sources
• Need dramatically better support at the level of
  metadata
• The ability to query and integrate across
  different conceptual systems
• The currently preferred answer is The Semantic
  Web, based on description logic
• will not work
• How tag blood? how tag gene?

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Application ontology

• cannot solve the problems of database
  integration
• There can be no mechanical solution to the
  problems of data integration
• in a domain like medicine
• or in the domain of really existing commercial
  transactions

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The problem in every case

• is one of finding an overarching framework for
  good definitions,
• definitions which will be adequate to the
  nuances of the domain under investigation

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Application ontology

• Ontologies are Applications running in real time

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Application ontology

• Ontologies are inside the computer
• thus subject to severe constraints on expressive
  power
• (effectively the expressive power of description
  logic)

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Application ontology cannot solve the
data-integration problem

• because of its roots in knowledge
  representation/knowledge mining

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different conceptual systems
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need not interconnect at all
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we cannot make incompatible concept-systems
interconnect
just by looking at concepts, or knowledge we
need some tertium quid
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Application ontology

• has its philosophical roots in Quines doctrine
  of ontological commitment and in the internal
  metaphysics of Carnap/Putnam
• Roughly, for an application ontology the world
  and the semantic model are one and the same
• What exists what the system says exists

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Quineanism

• ontology is the study of the ontological
  commitments or presuppositions embodied in
  scientific theories (or in the beliefs of
  experts)

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Quineanism, too, faces the integration problem

• If an ontology is the set of ontological
  commitments of a theory, how can we cope with
  questions pertaining to the relations between the
  objects to which different theories are
  committed?
• (Recall the Vienna Circle program of the Unity
  of Science)

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What is needed

• is some sort of wider common framework
• sufficiently rich and nuanced to allow concept
  systems deriving from different theoretical/data
  sources to be hand-callibrated

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What is needed

• is not an Application Ontology
• but
• a Reference Ontology
• (something like old-fashioned metaphysics)

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Reference Ontology

• An ontology is a theory of a domain of entities
  in the world
• Ontology is outside the computer
• seeks maximal expressiveness and adequacy to
  reality
• and sacrifices computational tractability for
  the sake of representational adequacy

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Belnap

• it is a good thing logicians were around before
  computer scientists
• if computer scientists had got there first,
  then we wouldnt have numbers
• because arithmetic is undecidable

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It is a good thing

• Aristotelian metaphysics was around before
  description logic, because otherwise
• we would have only hierarchies of
• concepts/universals/classes and no individual
  instances

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Reference Ontology

• a theory of the tertium quid
• called reality
• needed to hand-callibrate database/terminology
  systems

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Methodology

• Get ontology right first
• (realism descriptive adequacy rather powerful
  logic)
• solve tractability problems later

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The Reference Ontology Community

• IFOMIS (Leipzig)
• Laboratories for Applied Ontology (Trento/Rome,
  Turin)
• Foundational Ontology Project (Leeds)
• Ontology Works (Baltimore)
• BORO Program (London)
• Ontek Corporation (Buffalo/Leeds)
• LandC (Belgium/Philadelphia)

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Domains of Current Work

• IFOMIS Leipzig Medicine
• Laboratories for Applied Ontology
• Trento/Rome Ontology of Cognition/Language
• Turin Law
• Foundational Ontology Project Space, Physics
• Ontology Works Genetics, Molecular Biology
• BORO Program Core Enterprise Ontology
• Ontek Corporation Biological Systematics
• LandC NLP

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Recall

• GDB a gene is a DNA fragment that can be
  transcribed and translated into a protein
• Genbank a gene is a DNA region of biological
  interest with a name and that carries a genetic
  trait or phenotype
• (from Schulze-Kremer)

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Ontology

• Note that terms like fragment, region,
  name, carry, trait, type
• along with terms like part, whole,
  function, substance, inhere
• are ontological terms in the sense of traditional
  (philosophical) ontology

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Some Historical Background
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Aristotle
First ontologist

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First ontology (from Porphyrys Commentary on
Aristotles Categories)
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Linnaean Ontology
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Edmund Husserl
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Formal Ontology

• term coined by Husserl
• the theory of those ontological structures
• such as part-whole, universal-particular
• which apply to all domains whatsoever
• Formal ontology theory of things
• Formal logic theory of truths

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Husserl outlines a new methodof constituent
ontology

• to study a domain ontologically
• is to establish the parts of the domain
• and the interrelations between them
• especially the dependence relations
• (assembly structures, modules)

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Ontological Dependence

• a wife is dependent on a husband
• a king is dependent on his subjects
• a color is dependent on an extension
• a charge is dependent on a conductor
• a speech act is dependent on a speaker

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Logical Investigations1900/01

• Aristotelian theory of universals and particulars
• theory of part and whole
• theory of ontological dependence
• the theory of boundaries and fusion

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Formal Ontology

• contrasted with material or regional ontologies
• (compare relation between pure and applied
  mathematics)
• Husserls idea
• If we can build a good formal ontology, this
  should save time and effort in building reference
  ontologies for each successive domain

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Roman Ingarden

• Material Ontology
• Theory of Causality
• Theory of Relatively Isolated Systems

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Organisms

• order to be able to sustain themselves
  effectively as identical through time, must be at
  least in some respects bounded off from the
  surrounding world and partially isolated or
  shielded from it.

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Each multi-cellular organism

• is a system of relatively isolated causal systems
  organized in modular fashion in such a way as to
  contain within itself further relatively isolated
  causal systems on successively lower levels.
• The systems within this modular hierarchy are
  both partially interconnected (they collaborate
  in their functioning)
• and also partially segregated via coverings or
  membranes which protect their interiors from
  certain external influences and also allow other
  kinds of influences and substances to pass
  through them

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Bodily systems

• are not absolutely closed off from each other
  they are partially open and partially shielded.
• There are paths between them along which a
  certain restricted spectrum of causal influences
  and substances may flow.
• Each sense organ is a partially open system
  which is attuned to a special selection of
  outside processes and at the same time also
  shielded in other respects.

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Basic Formal Ontology

• BFO
• The Vampire Slayer

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Basic Formal Ontology

• Aristotelian theory of universals and instances
• theory of part and whole
• theory of ontological dependence
• theory of boundary, continuity and contact/fusion
• theory of states, powers, qualities, roles,
  functions, systems
• dual ontology of endurants and perdurants
• theory of environments/niches/contexts and
  spatial and spatio-temporal regions

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BFO

• not just a system of categories
• but a formal theory
• with definitions, axioms, theorems
• designed to provide the resources for reference
  ontologies for specific domains
• the latter should be of sufficient richness that
  terminological incompatibilities can be resolves
  intelligently rather than by brute force

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Three types of reference ontology

• 1. formal ontology framework for definition of
  the highly general concepts such as object,
  event, part employed in every domain
• 2. domain ontology, a top-level theory with a few
  highly general concepts from a particular domain,
  such as genetics or medicine
• 3. terminology-based ontology, a very large
  theory embracing many concepts and inter-concept
  relations

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MedO medical domain ontology

• universals and instances and normativity
• theory of part and whole and absence
• theory of ontological dependence
• theory of boundaries/membranes
• theory of states, powers, qualities, roles,
  (mal)functions, bodily systems
• dual ontology of endurants and perdurants
  anatomy and physiology
• theory of environments inside and outside the
  organism

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MedO

• including sub-ontologies
• cell ontology
• drug ontology
• protein ontology
• gene ontology

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and sub-ontologies

• anatomical ontology
• epidemiological ontology
• disease ontology
• therapy ontology
• pathology ontology
• the whole designed to give structure to the
  medical domain
• (currently medical education comparable to
  stamp-collecting)

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If sub-domains like these

• cell ontology
• drug ontology
• protein ontology
• gene ontology
• are to be knitted together within a single
  theory,
• then we need also a theory of granularity

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Testing the BFO/MedO approach

• within a software environment for NLP of
  unstructured patient records
• collaborating with
• Language and Computing nv (www.landc.be)

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LC

• LinKBase worlds largest terminology-based
  ontology
• incorporating UMLS, SNOMED, etc.
• LinKFactory suite for developing and managing
  large terminology-based ontologies

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LCs long-term goal

• Transform the mass of unstructured patient
  records into a gigantic medical experiment

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LinKBase

• LinKBase still close to being a flat list
• BFO and MedO designed to add depth, and so also
  reasoning capacity
• by tagging LinKBase terms with corresponding
  BFO/MedO categories
• by constraining links within LinKBase
• by serving as a framework for establishing
  relations between near-synonyms within LinKBase
  derived from different source nomenclatures

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So what is the ontology of blood?
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We cannot solve this problem just by looking at
concepts (by engaging in further acts of
knowledge mining)
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concept systems may be simply incommensurable
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the problem can only be solved
by taking the world itself into account
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A reference ontology

• is a theory of reality
• But how is this possible?
• How can we get beyond our concepts?
• answer ontology must be maximally opportunistic

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Maximally opportunistic

• means
• draw on 2 millennia of philosophical research
• pertaining to realism, scepticism, error, theory
  change, and the language/concept/world relation
• but also pertaining to the structure of reality
  itself and to the relations between different
  scientific disciplines

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Maximally opportunistic

• means
• dont just look at beliefs
• look at the objects themselves
• from every possible direction,
• formal and informal
• scientific and non-scientific

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It means further

• looking at concepts and beliefs critically
• and always in the context of a wider view which
  includes independent ways to access the objects
  at issue at different levels of granularity
• including physical ways (involving the use of
  physical measuring instruments)

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And also

• taking account of tacit knowledge of those
  features of reality of which the domain experts
  are not consciously aware
• look not at concepts, representations, of a
  passive observer
• but rather at agents, at organisms acting in the
  world

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Maximally opportunistic

• means
• look not at what the expert says
• but at what the expert does
• Experts have expertise knowing how
• Ontologists skilled in extracting knowledge that
  from knowing how
• The experts dont know what the ontologist knows

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Maximally opportunistic

• means
• look at the same objects at different levels of
  granularity

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We then recognize

• that the same object can be apprehended at
  different levels of granularity
• at the perceptual level blood is a liquid
• at the cellular level blood is a tissue

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select out the good conceptualizations

• those which have a reasonable chance of being
  integrated together into a single ontological
  system because they are
• based on tested principles
• robust
• conform to natural science

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Partitions should be cuts through reality

• a good medical ontology should NOT be compatible
  with a conceptualization of disease as caused by
  evil spirits

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Part Two

• Some Implications of Reference Ontology
• for Agent-Based and Situated Computing

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Agents

• organisms and (relatively isolated) computer
  systems
• situated in an environment
• capable of flexible, autonomous action in that
  environment
• interacting with other agents, including
• communicating, negotiating, coordinating
• often within some organizational context (e.g. a
  marketplace)

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• The agent interacts with its environment in two
  ways
• 1. it gathers sensory input throughsensors
• 2. it influences the environment by output
  actions through effectors (Wooldridge)

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Intelligence

• Intelligent or rational agents are characterised
  by
• an optimally adaptive behaviour in a changing
  environment. (Russell and Norvig)
• flexible behaviour (Wooldridge)
• Both definitions of intelligence presuppose an
  environment in which the agent operates.

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Flexibility

• a. reactivity able to respond quickly to changes
  in the environment
• b. pro-activeness behaviour is goal-oriented,
  and the agent is able to take the initiative in
  achieving ist goals
• c. social ability the capability to interact
  with other agents, i.e. to communicate

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Multiple agents share the same environment

• Thus they must coordinate their actions
• using communication protocols such as KQML
• based on the speech act theory of Austin and
  Searle

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KQML

• three types of performatives
• 1) Discourse performatives used in knowledge
  exchange type of conversation (e.g. ask-if, tell
  )
• 2) Intervention and mechanics of conversation
  performatives used to intervene in a dialogue
  (error, sorry) or to override default protocol
  (standby, ready)
• 3) Facilitation and networking performatives
  allow agents to find other agents that can handle
  their queries (forward, broker-one)

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Communication protocols

• involve components such as
• 1. sender
• 2. receiver
• 3. communication language
• 4. message
• 5. encoding/decoding functions
• 6. actions to be taken by receiver

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Austin and Searle

• saw their work as a contribution not to ontology
  but to the philosophy of language
• is concerned above all to combat a certain view
  of language
• (of Aristotle and Frege)
• according to which all utterances are assertives

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Austin

• The primary unit of philosophical analysis is
  linguistic
• using language is acting
• But what is the ontology of this sort of complex
  whole?

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Ontological structures

• in the social realm are transcategorial
• involving experiences (speaking, perceiving),
  intentions, language, action, deontic powers,
  background collective habits, mental competences,
  records

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Husserls theory of part, whole and dependence

• applied by Ingarden to physics, biology
• applied by Husserl himself to the ontological
  structure of linguistic meaning/grammar
• ? invention of categorial grammar,
• later formalized by Ajdukiewicz, Lambek

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Husserls theory of part, whole and dependence

• applied by his student Adolf Reinach to the
  ontological structure of law and of speech acts
• ? invention of speech act theory in Reinachs A
  Priori Foundations of the Civil Law in 1913

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Speech Acts

• Examples requesting, questioning, answering,
  ordering, imparting information, promising,
  commanding, baptising
• acts of the mind which do not have in words
  and the like their accidental additional
  expression
• but rather acts which are performed in the very
  act of speaking

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Reinachs theory of social acts

• part of a complete a priori ontology of social
  interaction
• a theory of actions, agents, ogligations, laws

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Some events depend on underlying states

• An assertion depends upon an underying state of
  conviction/belief
• A command depends upon an underlying relational
  state of authority

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Some events give rise to states

• Perception gives rise to conviction/belief as
  its successor state John sees that Mary is
  swimming
• Promising gives rise to claim and obligation as
  its successor states

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The Structure of the Promise
promisee
promiser
relations of one-sided dependence
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The Structure of the Promise
promisee
promiser
three-sided mutual dependence
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The Structure of the Promise
two-sided mutual dependence
oblig-ation
claim
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The Structure of the Promise
action do F
tendency towards realization
oblig-ation
claim
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Modifications of Social Acts

• Sham promises
• Lies as sham assertions (cf. a forged signature)
  rhetorical questions
• Social acts performed in someone elses name
  (representation, delegation)
• Social acts with multiple addresses
• Conditional social acts

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Collective social acts

• Singing in a choir
• Conversation
• Dancing
• Arguing
• Religious rituals

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How modific-ations occur
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How modific-ations occur
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How modific-ations occur
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How modific-ations occur
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Agents

• organisms and relatively isolated computer
  systems
• situated in an environment
• capable of flexible, autonomous action in that
  environment
• interacting with other agents, including
• communicating, negotiating, coordinating actions
• often within some organizational context (e.g. a
  marketplace)

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Environments a Neglected Major Category in the
History of Ontology

• Substances
• States, Qualities, Powers, Roles
• Processes
• Environments
• environments missing from Aristotle, from
  entity-relationship models

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Orthodox methodology

• described by one of its critics,
• Rodney Brooks,
• as the SMPA view

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SMPA

• Sense Model Plan Act
• the agent first senses its environment through
  sensors
• then uses this data to build a model of the world
• then produces a plan to achieve goals
• then acts on this plan

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SMPA

• belongs to the same methodological universe as
  Application Ontology
• If we want to build an intelligent agent, there
  need to be representations inside the agent
• of the domain within which the agent acts
• The agent reasoning processes act not on the
  real-world environment but on these
  representations (models)

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Brooks Engineering Approach

• takes its inspiration from evolutionary biology
• lends very little weight to the role of
  representations or models
• AI should use the world in all its complexity in
  producing systems that react directly to the world

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Engineering Approach

• An intelligent system embodies a number of
  distinct layers of activity (compare faculties
  of the mind, plus sensor-motoric faculties)
• These layers operate independently and connect
  directly to the environment outside the system
• Each layer operates as a complete system that
  copes in real time with a changing environment
• Layers evolve through interaction with the
  environment (artificial insects/vehicles )

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Brooks An intelligent system

• must be situated
• it is situatedness which gives the processes
  within each layer meaning
• Most importantly
• the world serves to unify the different layers
  together and to make them compatible/mutually
  adjusting

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Organisms, especially humans,

• fix their beliefs not only in their heads but in
  their worlds, as they attune themselves
  differently to different parts of the world as a
  result of their experience. And they pull the
  same trick with their memories, not only by
  rearranging their parsing of the world (their
  understanding of what they see), but by marking
  it.
• They place traces out there which changes what
  they will be confronted with the next time it
  comes around. Thus they don't have to carry their
  memories with them.
• Intelligence without Representation

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J. J. Gibson The Ecological Approach to Visual
Perception

• we are like (multi-layered) tuning forks tuned
  to the environment which surrounds us
• (we have evolved in such a way as to be attuned
  to our environment
• we are all experts in common sense
• our perceptual beliefs are almost always true)

120
Organisms are tuning forks

• They have evolved to resonate automatically and
  directly to those quality regions in their niche
  which are relevant for survival
• -- perception is a form of automatic resonation
• -- cognitive beings resonate to speech acts and
  to linguistic records
• -- cognitive beings resonate deontically

121
The Ecological Approach

• To understand cognition we should study the
  moving, acting organism as it exists in its
  real-world environment
• and for human organisms this is a social
  environment which includes records and traces of
  prior actions in the form of communication
  systems (languages), storage systems (libraries),
  transport systems (roads), legal systems

122
Gibson Environment as Array of Affordances

• The affordances of the environment are what it
  offers the animal, what it provides or furnishes,
  either for good or evil.
• James J. Gibson, The Ecological Approach to
  Visual Perception
• The environment of a commercial organism includes
  affordances such as prices.

123
Gibsons theory of surface layout

• Niches systems of barriers, openings, pathways
  to which organisms are specifically attuned,
• Include temperature gradients, patterns of
  movement of air or water molecules,
  electro-chemical signals guiding the movements of
  micro-organisms
• But also traffic signs, instructions posted on
  notice boards or displayed on the computer screen
  

124
Application of the niche concept

• in biology, ecology
• in medicine (embryology )
• in anthropology
• in economics
• in the ontology of artifacts
• in law
• in politics

125
Roger G. Barkers Eco-Behavioral Science

• Gibson Ecological Psychology of Perception
• Barker Ecological Psychology of Social Action
• P. Schoggen, Behavior Settings A Review and
  Extension of Roger G. Barkers Ecological
  Psychology. Stanford, CA Stanford University
  Press, 1989.

126
Roger Barker Niche as Behavioral Setting

• Niches are recurrent settings which serve as the
  environments for our everyday activities
• a newspaper kiosk in the morning rush-hour,
• your table in the cafeteria,
• the 5pm train to Long Island.

127
Behavior Settings

• Each behavior setting is associated with certain
  standing patterns of behavior.

128
Settings, for Barker,

• are natural units in no way imposed by an
  investigator.
• To laymen they are as objective as rivers and
  forests
• they are parts of the objective environment
  that are experienced as directly as rain and
  sandy beaches are experienced. (Barker 1968, p.
  11)

129
Unity of Behaviour and Ecological Setting

• A physical-behavioural unit is a unit its parts
  are unified together, but not through any
  similarity or community of substance.
• Transcategorial complexity of behavior and
  setting

130
Barker on Unity of Social Reality

• The conceptual incommensurability of phenomena
  which is such an obstacle to the unification of
  the sciences does not appear to trouble natures
  units.
• Within the larger units, things and events from
  conceptually more and more alien sciences are
  incorporated and regulated.

131
Barker on Unity of Social Reality

• As far as our behaviour is concerned, even
  the most radical diversity of kinds and
  categories need not prevent integration

132
The Systematic Mutual Fittingness of Behaviour
and Setting

• The behaviour and the physical objects are
  intertwined in such a way as to form a pattern
  that is by no means random there is a relation
  of harmonious fit between the standard patterns
  of behaviour occurring within the unit and the
  pattern of its physical components.

133
The Systematic Mutual Fittingness of Behaviour
and Setting

• The seats in the lecture hall face the speaker.
  The speaker addresses his remarks out towards the
  audience.
• The boundary of the football field is the
  boundary of the game.
• ? Non-transposability

134
Non-transposability

• This mutual fittingness of behaviour and
  physical environment extends to the fine,
  interior structure of behaviour in a way which
  will imply a radical nontransposability of
  standing patterns of behaviour from one
  environment to another.
• (Cant play football in a lecture theater)

135
Power and Authority

• forces which help to sustain this mutual
  fittingness and thus to constitute the unity of
  the physical-behavioural unit through time.
• These include physical constraints exercised by
  hedges, walls or corridors or by persons with
  sticks
• also social forces manifested in threats,
  promises, warnings, admonitions

136
Settings shape Persons

• Each person has many strengths, many
  intelligences, many social maturities, many
  speeds, many degrees of liberality and
  conservativeness, and many moralities, depending
  in large part on the particular contexts of the
  persons behavior.

137
Aurel Kolnai

• a human society
• comprehends the same individual over and over
  again in line with his various social
  affiliations
• What an agent is, depends on the agents
  environment

138
Daily life

• passage through a succession of
  physical-behavioural units
• The latter are as much a part of the furniture
  of reality as are garden-variety continuants and
  occurrents

139
Environments may be nested

• may have actual parts which are also
  environmental settings
• (hierarchical nesting)
• ? Theory of the organization of organizations
• the roles you take on as inhabitant of the niche
  called IBM
• the roles you take on as inhabitant of the niche
  called US-Division 4B/661 of IBM (YOU ARE THE
  BOSS)
• the roles you take on as inhabitant of the niche
  called your local office (YOU ISSUE COMMANDS)

140
Marks of (bodily) substance

1. Rounded-offness
2. Occupies space
3. Complete boundary
4. May have substantial parts (nesting)
5. May be included in larger substances
6. Has a life (manifests contrary accidents at
   different times)

141
Corresponding Marks of Niches (3-Dimensional
Environments)

• (i) A niche enjoys a certain natural completeness
  or rounded-offness,
• being neither too small nor too large
• in contrast to the arbitrary undetached parts
  of environmental settings and to arbitrary heaps
  or aggregates of environmental settings.

142
(ii) A niche takes up space,

• it occupies a physical-temporal locale,
• and is such as to have spatial parts.
• Within this physical-temporal locale is a
  privileged locusa hole
• into which the tenant or occupant of the setting
  fits exactly.

143
(iii) A niche

• has an outer boundary
• there are objects which fall clearly within it,
• and other objects which fall clearly outside it.
  
• (The boundary itself need not be crisp.)

144
(iv) A niche

• may have actual parts which are also
  environmental settings
• Barker Many settings occur in assemblies. A
  unit in the middle range of a nesting structure
  is simultaneously both whole and part, both
  entity and environment.
• Compare the hierarchical organization of the
  human body into organs, cells,

145
(v) A niche

• may be a proper part of larger, circumcluding
  niche.

146
(vi) A niche has a lifeNiches are
endurants/continuants

• is now warm, now cold
• now at peace, now at war .
• now expanding, now contracting

147
Marks of (bodily) substance

1. Rounded-offness
2. Occupies space
3. Complete boundary
4. May have substantial parts (nesting)
5. May be included in larger substances
6. Has a life is now warm, now cold (Substances are
   endurants/continuants)

148
On being in a niche

• Niches are in some ways like the interiors of
  substances
• Two concepts of car
• John is in his car
• John saw his car from a distance
• The embryo is in the uterus
• The doctor examined the uterus

149
Two concepts of London

• John is in London
• John saw London from the air
• London ? London
• IBM ? IBM
• A is part of B vs. A is in the interior of B as a
  tenant is in its niche

150
3-dimensional environments

• England
• The Nile Delta
• The interior of your car
• A stagnant pond
• ecologists habitat

151
4-dimensional environments

• Lobsters have evolved into environments marked
  by cyclical patterns of temperature change
• Tudor England
• The Afghan winter
• The window of opportunity for an invasion of
  Iraq
• Barkers behavior settings

152
Where are Niches?
153
SNAP Ontology of entities enduring through time
154
Where are Places?
155
Where are behavior-settings?
spatio- temporal volumes
156
SPAN Ontology of entities extended in time
spatio- temporal volumes
standardized patterns of behavior
157
Three Main Ingredients to the SNAP/SPAN Framework

• Independent SNAP entities Substances
• Dependent SNAP entities powers, qualities,
  roles, functions
• SPAN entities Processes

158
Gene Ontology

• Cellular Component Ontology subcellular
  structures, locations, and macromolecular
  complexes
• examples nucleus, telomere
• Molecular Function Ontology tasks performed by
  individual gene products
• examples transcription factor, DNA helicase
• Biological Process Ontology broad biological
  goals accomplished by ordered assemblies of
  molecular functions
• examples mitosis, purine metabolism

159
Three Main Ingredients to the SNAP/SPAN Framework

• Independent SNAP entities Molecular Components
• Dependent SNAP entities Functions
• SPAN entities Processes

160
Conclusions for a Theory of Agents

• Two sorts of ontology for a theory of agents
• Domain ontology (ontology within the agent)
• Reference ontology (including both agents and
  environment within a single theory)
• Communication between agents constructed within
  different information systems environments
  achieved only via hand-callibration of their
  communication protocols via something like a
  reference ontology

161
Conclusions for a Theory of Agents

• Agents are in the world, they have to achieve
  their goals in relation to a particular
  environment, and adapt to this environment
• Therefore if we want to have a good theory of
  agent-based computing, we need to have a good
  theory of (worldly) environments

162
Humans, Machines, and the Structure of Knowledge

• Harry M. Collins
• SEHR, 4 2 (1995)

163
Knowledge-down-a-wire

• Imagine a 5-stone weakling having his brain
  loaded with the knowledge of a champion tennis
  player.
• He goes to serve in his first match
• -- Wham!
• his arm falls off.
• He just doesn't have the bone structure or
  muscular development to serve that hard.

164
Types of knowledge/ability/skill

• those that can be transferred simply by passing
  signals from one brain/computer to another.
• those that cant

165
Sometimes it is the body (the hardware) which
knows
166
and sometimes it is the world outside which knows
167
Types of knowledge/ability/skill

• those that can be transferred simply by passing
  signals from one brain/computer to another.
• those that cant
• -- here the "hardware" is important
• abilities/skills contained
• (a) in the body
• (b) in the world

168
From

• The Methodological Solipsist Approach to
  Information Processing
• To
• The Ecological Approach to Information Processing

169
Fodorian Psychology

• To understand human cognition we should study the
  mind/brain in abstraction from its real-world
  environment
• (as if it were a hermetically sealed Cartesian
  ego)

170
Shimon Edelmans Riddle of Representation

• two humans, a monkey, and a robot are looking at
  a piece of cheese
• what is common to the representational processes
  in their visual systems?

171
Answer
The cheese, of course
172
I know where the book is

• I know how to find it
• I know what the square root of 2489 is
• I know how to calculate it
• I know how to recognize the presence of a tiger
• by smell, noise (in real-world context)

173
How to solve this problem

• Compare the way in which the physical properties
  of ROADS help people to obey the traffic laws
  when driving
• Deal with obligations, norms not via deontic
  logic but via the comparison with roads?