Autonomous Agents

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Autonomous Agents

• Overview

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Topics

• Theories logic based formalisms for the
  explanation, analysis, or specification of
  autonomous agents.
• Languages agent-based programming languages.
• Architectures integration of different
  components into a coherent control framework for
  an individual agent.

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Topics

• Multi-agent architectures methodologies and
  architectures for group of agents (could be from
  different architectures)
• Agent modeling modeling other agents behavior
  or mental state from the perspective of an
  individual agent
• Agent capabilities
• Agent testbeds and evaluation

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Agent Theories, Languages, and Architectures

• Wooldridge Jennings
• (ATAL 1994, LNAI 890)

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What is an agent?

• Weak
• Autonomy
• Social ability
• Reactivity
• Pro-activities
• Strong
• Mental properties such as knowledge, belief,
  intention, obligation
• Emotional
• Others attributes mobility, veracity,
  benevolence, rationality

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Agent Theories

• How to conceptualize agents?
• What properties should agents have?
• How to formally represent and reason about agent
  properties?

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Agent Theories

• Definition an agent theory is a specification
  for an agent.
• ? Formalisms for representing and reasoning
  about agent properties
• Starting point agent entity which appears to
  be the subject of beliefs, desires, etc.

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Intentional system

• An intentional system whose behavior can be
  predicted by the method of attributing belief,
  desires, and rational acumen
• Proved that can be used to describe almost
  everything
• Good as an abstract tool for describing,
  explaining, and predicting the behavior of
  complex systems

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Intentional system - Examples

• One studies hard because one wants to get good
  GPA.
• One takes the course cs579-robotic because one
  believes that it will be fun.
• One takes the course cs579-robotic because
  there is no 500-level course offered.
• One takes the course cs579-robotic because one
  believes that the course is easy ?

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Agent Attitudes

• Information attitudes related to the information
  that an agent has about the environment
• Belief
• Knowledge
• Pro-attitudes guide the agents actions
• Desire
• Intention
• Obligation
• Commitment
• Choice
• An agent should be represented in terms of at
  least one info-attitude and one pro-attitude. Why?

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Representing intentional notions

• Representing
• Jan believes Cronos is the father of Zeus
• naïve translation into FOL
• Believe(Jan, Father(Zeus,Cronos))
• Problems
• No nested predicate
• Zeus Jupiter
• Believe(Jan, Father(Jupiter,Cronos)) Wrong
• Conclusion FOL is not suitable since intention
  is context dependent.

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Possible World Semantics

• Hintikka 1962 Agents belief can be
  characterized as a set of possible worlds.
• Example
• A door opener robot door is closed, lock needs
  to be unlocked but the robot does not know if the
  lock is unlocked or not two possibilities
• closed, locked
• closed, unlocked
• Card player (poker) ?
• UNIX Ping command ?

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Possible World Semantics

• Each world represents a state that the agent
  believes it might be in given what it knows.
• Each world is called a epistemic alternative.
• The agent believes in something is true in all
  possible worlds.
• Problem logical omniscience agent believes all
  the logical consequences of its belief ?
  impossible to compute.

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Alternatives to PWS

• Levesque belief and awareness explicit belief
  (small) from implicit belief (large).
• No nested belief
• The notion of a situation is unclear
• Under certain situation unrealistic prediction
• Konolige the deduction model modeling the
  belief of a symbolic AI system (database of
  beliefs and an inference system).
• Simple

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Others

• Meta-language one in which it is possible to
  represent the properties of another language
• Problem inconsistency
• Pro-attitudes goals and desires adapting
  possible world semantics to model goals and
  desires
• Problem side effects

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Theory of agency

• Realistic agent
• combination of different components
• dynamic aspect
• Moore knowledge and action study the problem
  of knowledge precondition for actions
• I needs to know the telephone number of my friend
  Enrico in order to call him.
• I can find the telephone number in the telephone
  book.
• I needs to know that the course is easy before I
  sign up for it ?

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Theory of agency

• Cohen and Levesque belief and goal originally
  developed as a pre-requisite for a theory of
  speech acts but proved very useful in analysis of
  conflict and cooperation in multi-agent
  diaglogue, cooperative problem solving

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Theory of agency

• Rao and Georgeff belief, desire, intention
  (BDI) architecture logical framework for agent
  theory based on BDI, used a branching model of
  time
• Singh logics for representing intention, belief,
  knowledge, know-how, communication in a
  branching-time framework

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Theory of agency

• Werner general model of agency based on work in
  economics, game theory, situated automate,
  situated semantics, philosophy.
• Wooldridge modeling multi-agent system

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Agent Architectures

• Construction of computer systems with properties
  specified by an agent theory.
• Three well-know architectures
• Deliberative
• Reactive
• Hybrid

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Deliberative architecture

• View agent as a particular type of knowledge
  based system known as symbolic AI
• Contains an explicit represented, symbolic model
  of the world
• Decision is made via logical reasoning (pattern
  matching, symbolic manipulation)
• Properties
• Attractive from the logical point of view
• High computational complexity (FOL not
  decidable, with modalities highly undecidable)

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• Sense
• Assimilate
• Sensing results

• Reasoning
• Symbolic
• representation
• of the world
• Determine what
• to do next

• Act
• Execute the
• action generated
• by the reasoning
• module

ENVIRONMENT
Deliberative architecture in picture
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Deliberative architecture

• Examples
• Planning agents a planner is an essential
  component of any artificial agent
• Main problem intractability addressed by
  techniques such as hierarchical, non-linear
  planning.
• IRMA (Intelligent Resource-bounded machine
  architecture) explicit representations of BDI
  planning library, a reasoner, opportunity
  analyser, a filtering process, a deliberation
  process (mainly reduced the time to deliberate)

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Deliberative architecture

• HOMER a prototype of an agent with linguistic
  capability, planning and acting capability.
• GRATE layered architecture in which the
  behavior of an agent is guided by the mental
  attitudes of beliefs, desires, intentions, and
  joint intention.

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Reactive architecture

• Proposed to overcome the weakness of symbolic AI
• Main features
• does not include any kind of central symbolic
  world model
• does not use complex reasoning

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• Sense
• Assimilate
• Sensing results

• Reasoning
• Determine what
• to do next

• Act
• Execute the
• action generated
• by the reasoning
• module

ENVIRONMENT
Reactive architecture in picture
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Reactive architecture

• Brook - behavior language subsumption
  architecture
• Hierarchy of task-accomplishing behaviors
• Each behavior competes with others
• Lower layer represents more primitive task and
  has precedence over upper layers
• Very simple
• Demonstrate that it can do a lot
• Multiple subsumption agents

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Reactive architecture

• Arge and Chapman PENGI most everyday activity
  is routine
• Once learned, a task becomes routine and can be
  executed with little or no modification
• Routines can be compiled into a program and then
  updated from time to time (e.g. after new tasks
  are added)

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Reactive architecture

• Rosenschein and Kaelbling - Situated automata
• Agent is specified in declarative terms which are
  then compiled into digital machine
• Correctness of the machine can be proved
• No symbol manipulation in situated automata, thus
  efficient
• Maes Agent network architecture an agent is a
  network of competency modules

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Hybrid architecture

• Combine deliberative and reactive architecture
  exploit the best out of the two
• Georgeff and Lansky Procedural Reasoning
  System BDI plan library, explicit symbolic
  representation of BDI
• Beliefs are facts FOL
• Desires are represented by behavior
• Each plan in the plan library is associated with
  invocation condition ? reactive
• Intention the set of currently active plans

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Environment
Plan Library
Belief FOL
P1 Invocation I1
System Interpreter
Desire System beha.
Pn Invocation In
Active
Intention
Pi Invocation Ii
Pj Invocation Ij
PRS in picture
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Hybrid architecture

• Ferguson TOURINGMACHINES
• Perception and action subsystem interact
  directly with the environment
• Control framework system three control layers
  each is independent, activity producing,
  concurrently executing process
• Reactive layer (response to events that happen
  too quickly for other to response)
• Planning layer (select plan, actions to achieve
  goal)
• Modeling layer (symbolic representation, use to
  resolve goal conflict)

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Hybrid architecture

• Burmeister et al. COSY hybrid BDI with
  features of PRS and IRMA, for a multi-agent
  testbed called DASEDIS
• Mueller et at. INTERRAP layered architecture,
  each layer is divided into knowledge and control
  vertical part

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Agent language

• A system that allows one to program hardware and
  software computer systems in terms of some of the
  concepts developed by agent theorists.
• Shoham agent-oriented programming
• A logical system for defining the mental state of
  agents
• An interpreted programming language for
  programming agents
• An agentification process, for compiling agent
  program into low-level executable systems
• ? Agent0 first two features

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Agent language

• Thomas PLACA (Planning communicating agent
  language)
• Fisher Concurrent METATEM correctness of the
  agents with respect to their specification
• IMAGINE project ESPIRIT
• General Magic, Inc. TELESCRIPT
• Connah and Wavish - ABLE