Challenges for Effective Open Virtual Organisations

1
Challenges for Effective Open Virtual
Organisations

• Timothy J. Norman
• Department of Computing Science
• University of Aberdeen
• t.j.norman_at_abdn.ac.uk
• 8th Annual International Workshop on Engineering
  Societies in the Agents World

2
Outline

• Open Virtual Organisations
• ADEPT
• CONOISE/CONOISE-G
• e-Institutions
• Semi-Structured Processes in Open Societies
• Challenge 1 machine-readable organisations
• Challenge 2 recognising the inevitability of
  conflict
• Challenge 3 machinery for resolving conflicts
• Towards mixed initiative (Human-Agent) VOs
• Conclusions

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Open Virtual Organisations

• What are OVOs?
• Open systems components (agents) may come and
  go
• Organisation system has some degree of
  established structure operation
• A tension
• Suppose some agent plays a unique role in an
  organisation that agent leaves!
• Suppose a new agent appears offering a new
  service restructure the organisation?

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Society vs. Process
society
open
closed
process
closed
open
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ADEPT
Business process
Organisational structure
gt Service descriptions
(service name Vet_Customer inputs (
CCL_Customer customer_details cli man )
outputs( CCL_Decision verdict ) guard ("")
body ( sequence check_CCL ( details
servicecustomer_details
serviceverdict limit ) -gt (
check_CCL ) ) )

• gt Enactment through
• SLA negotiation
• Service task execution
• renegotiation

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ADEPT -

• Decentralised workflow management
• Flexibility task/service scheduling, automated
  SLA (re-)negotiation
• Process fixed at design time
• System organisation
• Services
• No workflow-level operational constraints or
  analysis
• Throughput
• Service delivery times
• Quality control

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Society vs. Process
Example 2 CONOISE CONOISE-G Domain telecom
services configuration. T. J. Norman, A. Preece,
S. Chalmers, N. R. Jennings, M. Luck, V. D. Dang,
T. D. Nguyen, V. Deora, J. Shao, W. A. Gray and
N. J. Fiddian. (2004). Agent-based formation of
virtual organisations, Knowledge-Based Systems
17103111.
Increased system flexibility/adaptation
society
open
Increased need to manage trust (security
privacy more complex)
Increased heterogeneity of system components
closed
ADEPT
process
closed
open
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CONOISE

• Package required by customer
• Movie subscription
• News service
• gt50 free text messages per month
• ?30 free phone minutes per month

• Offers received
• SP1 10 movies pcm, hourly news
• SP2 hourly news
• SP3 120 texts AND 30 mins
• SP4 5 movies pcm, 30 mins

• Quality of offers assessed
• Best offer combination identified through reverse
  auction

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CONOISE

• Open system
• Agents may come and go
• New services (or service packages) may be offered
• Open process
• VOs exist for lifetime of service
• Workflows composed of chained VOs
• No designed-in organisational structure
• All agents are peers in competition
• ADEPT-like workflow structure can emerge

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Society vs. Process
Lets look a bit closer at this space
society
Example 3 e-Institutions Agents may come and go
Governed by institutional rules Process defined
by institution A. García-Camino, J.-A.
Rodríguez-Aguilar, C. Sierra, and W. Vasconcelos.
(2006). Norm-Oriented Programming of Electronic
Institutions. Int. Joint Conf. Autonomous Agents
and Multi-Agent Systems.
open
closed
ADEPT
process
closed
open
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Closed or Open Processes?
Institution engenders trust (but agents must
trust institution) Agents not permitted to act
outside the protocol Security and privacy of
information honoured Quality control
e-Institutions encapsulate common episodal
processes why require agents to coordinate
these at run-time?
Agents must decide who to trust Failure may
affect reputation ? distrust What can/should be
done how information is used must be agreed
But which e-Institution offers the coordination
services required?
Challenge 1 Institutional rules/policies must be
machine-understandable
society
open
e-Institutions
processes
closed
open
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Semi-Structured Processes
Machine-understandable institutions M. J.
Kollingbaum T. J. Norman (2002). Supervised
Interaction, AAMAS

• A language for describing contracts

• Reasoning machinery to interpret and negotiate
  contracts

• Institutional elements to host contract
  enactment

society
open
e-Institutions
process
closed
open
semi-structured
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Example eScience
a

• Project PI (agent a) has contract with funding
  body, ß, such that a is

ß

• Obliged to report experimental results

Oapireport_results(a, R)

• Forbidden from publishing source data

FXYpublish(D)
Fapiclaim(X) Papiclaim(staff_costs) Papiclaim(t
ravel)

• Limited to spending project funds on staff and
  travel costs

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Example sub-contracting
d

• Suppose a needs to sub-contract a task to
  generate results
• It has two options

a
?
ß

• Agent ? is a publicly funded organisation that
  performs the task for free but requires data to
  be published

OXYpublish(D)
OXYpay(fee) we also know that pay(X) AR?AR
claim(X)

• Agent d is a private organisation that charges a
  fee

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Example conflict

• Regardless of what a does, it will violate the
  contract with ß

?
d
a
Challenge 2 agents must be able to recognise
conflict situations

• No sub-contract

ß

• Sub-contract to ?
• OXYpublish(D)

Oapireport_results(a, R) FXYpublish(D) Fapiclai
m(X) Papiclaim(staff_costs) Papiclaim(travel)
Oapireport_results(a, R) FXYpublish(D) Fapiclai
m(X) Papiclaim(staff_costs) Papiclaim(travel)
Oapireport_results(a, R) FXYpublish(D) Fapiclai
m(X) Papiclaim(staff_costs) Papiclaim(travel)

• Sub-contract to d
• OXYpay(fee)
• pay(X) AR?AR claim(X)

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Utilising Detected Conflicts

• Informs agent of the implications of signing a
  contract (adopting the policy of an
  e-Institution)
• Enables focussed deliberation on what to violate,
  and hence what sanctions may be imposed
• Agents have social autonomy
• Could also guide conflict resolution

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Conflict detection mechanisms

• NoA (Kollingbaum Norman)
• Normative Architecture
• Encodes possible plans and active norms in an
  adapted RETE network
• Efficiently identifies whether a new norm is in
  conflict and what with (given options for action)
• FOUND! (Vasconcelos, Kollingbaum Norman)
• First-Order Unification for Norm Deliberation
• Norms combined with constraints on their
  application and domain axioms
• Also tells us how the conflict can be resolved

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Example NEO
Non-combatant Evacuation Operation Reports are
received of NGO workers requiring assistance Top
priority mission to evacuate NGO workers Task
allocated to Team A commander Teams A and B are
different coalition partners

• Team A
• Based on carrier off coast (South)
• UAVs with sensors to provide on-going visual
  surveillance
• Group of helicopters within range of NGO workers

• Team B resources
• Based to the North-East on land
• Group of helicopters within range of NGO workers
• Mechanised infantry

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Example NEO Norms

• Most effective plan deploy UAV assess
  situation deploy helis coordinate with UAV
  intelligence
• Team A operates under the following norms
• Commander is obliged to evacuate the NGO workers
  (from NEO mission policy)
• Team A is forbidden from sharing UAV-obtained
  intelligence with other coalition partners (from
  coalition operations policy)
• Helicopters are forbidden from flying in bad
  weather (from safety policy)

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Example NEO Enactment

• AUV is deployed
• Information from flight operations deteriorating
  weather conditions
• Conflict
• Continuing with Heli operation from carrier would
  violate safety policy
• Delegating Heli evacuation to team B would
  violate coalition operations policy in sharing
  UAV intelligence
• Failing to continue with NEO will violate mission
  policy

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Need for Conflict Resolution

• Time and safety-critical scenario
• Norm violation not an option
• Must resolve conflict
• Automatically, or
• By requesting human intervention into the
  decision-making

Challenge 3 Agents should have machinery to
suggest resolutions to or to automatically
resolve conflicts
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Example Conflict Resolution

• FOUND! used to identify norm conflict
• FOUND! offers resolution on the basis of
  meta-policy (or conflict resolution strategy)
  legis superioris
• Proposal presented to Team A commander
• Curtail coalition operations policy regarding UAV
  intelligence sharing in this instance
• Delegate Heli evacuation of NGO workers to team B
• Instruct AUV intelligence group and team B Heli
  group to coordinate the rescue mission

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Human-Agent Teamwork

• This example
• Further demonstrates the utility of norm conflict
  detection and resolution
• Illustrates the need to refocus on teamwork
• But not agent teamwork (ala. Cohen Levesque
  Tambe etc.), humans and agents working as a team
• Agents can use these techniques to aid humans in
  making complex decisions
• Monitoring and restricting information flows
• Managing and supporting trusted virtual
  environments within which humans operate

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Summary

• Open Virtual Organisations need
• Models of Norms/Contracts/Policies that are
  machine-readable
• Mechanisms to efficiently identify norm conflicts
• Mechanisms to resolve conflicts, or to coherently
  present solutions to users

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Other Dimensions
Increased process complexity
This is where we need to go!
OVOs
Increased system scale
e-Institutions
process
closed
open
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Acknowledgements

• ADEPT (1995-1998) Nick Jennings
• CONOISE/CONOISE-G (2000-2006) Alun Preece (now
  Cardiff) Nir Oren (now KCL) Nick Jennings Mike
  Luck
• NoA (2000-2003) Martin Kollingbaum (now CMU)
• FOUND! Wamberto Vasconcelos (Aberdeen)
• ITA (International Technology Alliance)
  (2006-2016) Wamberto Vasconcelos, Derek
  Sleeman, Katia Sycara (CMU), Simon Parsons (CUNY)
• ALIVE (FP7) from 2008

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