Collectively Cognitive Agents Collectively Cognitive Agents in Cooperative Teamsin Cooperative Teams

Jacek Brzeziński, Piotr Dunin-KępliczInstitute of Computer Science, Polish Academy of Sciences

Barbara Dunin-KępliczInstitute of Computer Science, Polish Academy of Sciences

Institute of Informatics, Warsaw University

GoalsGoals

Simulator– Collective Commitment Theory (B. Dunin-Kęplicz, Verbrugge)

– Theory of Trust (Castelfranchi, Falcone)

Research of some BDI systems propertieswhen different definitions of collective commitments are used:– are agents willing to cooperate?– does the system evolve? – quality of teamwork?– how much information is needed for agents to

cooperate productively?– how to calculate the degree of trust?

OverviewOverview

Collective Commitments theorySimulator:– agents– interaction scenario– different CC models w.r.t. trust

Test resultsFuture work

Collective commitmentsCollective commitments

Tuning machine allows to select collective commitment type w.r.t.:– group awareness about social plan– group awareness about distribution of

bilateral commitments– existence of collective intention

Different models of organizations

Examples of collective commitmentExamples of collective commitment

Robust collective commitment

Weak collective commitment

Distributed commitment

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Roles of agentsRoles of agents

Managers– generate tasks (sets of actions) to be

performed by Workers for a specific salary– do not execute actions– delegate actions (or sets of actions) to other

agents (Workers)

Workers– perform actions– cannot delegate actions

Properties of agentsProperties of agents

Beliefs– believes(A, f) - agent A believes f

Intentions– intends(A, a) - agent A intends to perform action a

Abilities– able(A, a, n) - agent A is able to perform action a

(n - probability of success)

Trust– trusts(A, B, a, n) - agent A trusts in agent B to do a in degree of n

– trust values base on direct experience.

– Workers & Manager trust in Workers to execute specific actions.

– Workers trust in Manager to do proper team selection.

Four levels of CPSFour levels of CPSManager has a task (set of actions) to perform:1. Potential recognition

Manager recognizes potential for cooperative action in order to complete the task

2. Team formationManager attempts to establish group of agents that can collectively fulfil the goal (collective intention)

3. Plan generationSocial plan of achieving the goal is built and the collective commitment is formed

4. Team actionAgents involved do their tasks and eventually achieve the main goal

Potential recognitionPotential recognition

M sends CFP to all the Workers in the system (content = (O - set of actions))

Workers respond with their bids M chooses the best group G that can

perform the task collectively w.r.t.:– trust in Workers in the group– prices proposed by Workers – risk factor describing preferences of M

Team formation & plan generation 1Team formation & plan generation 1

M broadcasts relevant information to all Workers in G:– an offer to form a group– an offer to participate in task– an allocation of actions– division of task O into subtasks– an offer to perform action(s) for price x

Team formation & plan generation 2Team formation & plan generation 2

Agents decide whether to join the group Task result estimation function takes into account following factors:• trust in the manager M• trust in other members of the group• ability to perform delegated actions

If all Workers agree, then collective commitment is constructed.

Team actionTeam action

Workers perform actions and tell M about results

If all actions have succeeded, the task also succeeds and all Workers collect their payments

Results of actions are propagated to group members, depending on team awareness level

Agents modify their degrees of trust in other group members (basing on direct experience)

Robust collective commitmentRobust collective commitment

Information sent to Workers– an offer to create a group G with intention to realize

task O– an allocation of sets of actions– an offer to perform a set of actions for a price of x

Task result estimation function

Result propagation– All the information about successes and failures

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Weak collective commitmentWeak collective commitment

Information sent to Workers– an offer to create a group G with intention to realize

task O– a division of task O into subtasks S– an offer to perform a set of actions for a price of x

Task result estimation function

Result propagation– only failure information: agent, failed action, subset of O

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Distributed commitmentDistributed commitment

Information sent to Workers– an offer to perform a set of actions for a price

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Result propagation– only the team action result

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TestsTests

Configuration• 16 Workers, 1 Manager• 100,000 tasks• 4 actions in every task• abilities set randomly between 0.5 and 1• starting trust value = 1

Parameters• number of successful/failed contracts• efficiency• difference between trust values and real abilities

Test ResultsTest Results

Strong models of CC:– efficient–moderate number of contracts– agents learning from experience– costly (comm. resources)

Weak models– unstable–many contracts, mostly failing

Robust Collective CommitmentRobust Collective Commitment

Distributed CommitmentDistributed Commitment

Future workFuture work

Complex organization model– more managers– more detailed trust model– more complex commitment structure– institutional restrictions

Reconfiguration– role of trust

Dynamic commitment model evolution