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Designing Agent Societies Volha Bryl PhD student ICT, DIT

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1 Designing Agent Societies Volha Bryl PhD student ICT, DIT

2 Agent Society Agent Goals Capabilities ………… ………… ………… ………… + collaboration (through delegation) - competitive goals Society member’s objective: use others capabilities to achieve personal goals

3 Problem Find optimal assignments: satisfy all goals of all agents or reach an compromise?

4 Formalization (1) Two types: Actors and Goals Goals: an actor wants a goal to be satisfied Capabilities: an actor can satisfy a goal Communication: an actor can pass (or delegate) a goal to another actor

5 Formalization (2) Goals can be decomposed into subgoals  Only one possible decomposition  Goal is satisfied iff all its subgoals are satisfied  Decomposition can be performed by any actor  Decomposition is actor-independent

6 Formalization (3) Three basic actions:  an actor satisfies a goal  an actor passes (or delegates) a goal to another actor  an actor decomposes a goal into subgoals Solution is a list of actions that should be executed to satisfy all initial goals of all actors (or to reach an equilibrium)

7 Idea Let’s look at PLANNING which is in AI “the problem of finding a sequence of primitive actions to achieve some goal”

8 Planning problem we need to formalize actions an action has precondition and effect precondition and effect can be represented as conjunction or disjunction (for precondition only) of predicates or their negations

9 Planning problem. Predicates Actor’s capabilities  can_satisfy (a – actor, g – goal)  can_depend_on (a1 – actor, a2 – actor) Actor’s initial desires  wants (a – actor, g – goal) Possible decomposition of goals  can_be_decomposed (g – goal, g1 – goal, g2 – goal, …)

10 Planning problem. Actions 1) Satisfies (a – actor, g – goal) precondition (and can_satisfy (a, g) wants (a, g) ) effect (and done (g)* not (wants(a,g) ) * done (g – goal) is an additional predicate which means “goal g is satisfied, no one wants it anymore”

11 Planning problem. Actions 2) Decomposes * (a – actor, g – goal, g1 – goal, g2 – goal) precondition (and can_be_decomposed (g, g1, g2) wants (a, g) ) effect (and wants(a,g1) wants(a,g2) not (wants(a,g) ) * can be extended to more than two actions

12 Planning problem. Actions 3) Passes (a1 – actor, g – goal, a1 – actor) precondition (and can_depend_on (a1, a2) wants (a1, g) ) effect (and wants(a2, g) not (wants(a1, g) )

13 Planning problem. Intuition (1) wants (A, G) Decomposes (A, G, G1, G2) wants (A, G1) wants (A, G2) wants are propagated through the graph and then eliminated – become done

14 Planning problem. Intuition (2) wants (A, G) done (G) Satisfies (A, G) wants are propagated through the graph and then eliminated – become done wants (A, G)wants (B, G) Passes (G, A, B)

15 Example. Informal formulation I can buy a ticket I want to go to the conference …to go there means: buy a ticket and get reimbursement Professor Accounting office I can ask accounting office for help We can help to get the reimbursement

16 Example. PDDL formulation (define (problem example) (:domain tropos-domain) (:objects Professor Accounting_office - t_actor Go_to_conference Get_reimbursement Buy_ticket - t_goal ) (:goal (and (done Go_to_conference) ) ) (:init (can_do Accounting_office Get_reimbursement ) (can_do Professor Buy_ticket ) (can_depend_on Professor Accounting_office ) (wants Professor Go_to_conference ) (and_subgoal2 Go_to_conference Buy_ticket Get_reimbursement ) )

17 Example. Using the tool


19 Example. Solution decomposes [professor, go-to-conference, buy-ticket, get-reimbursement] performs [professor, buy-ticket] pass [professor, get-reimbursement, accounting-office] performs [accounting-office, get-reimbursement]

20 Big example. Description I need to write a letter to the UK embassy I know English I can use printer I have an official stamp I can only sign letters… Boss 1 st Secretary 2 nd Secretary 3 rd Secretary …to write a letter means: type, print and certify it with stamp and boss’s signature

21 Big example. Solution decomposes [boss, write-letter, send-letter, type-letter-in-english] decomposes [boss, send-letter, certify-letter, print-letter] pass [boss, type-letter-in-english, secretary-1] pass [boss, print-letter, secretary-1] performs [secretary-1, type-letter-in-english] decomposes [boss, certify-letter, stamp-letter, sign-letter] pass [boss, stamp-letter, secretary-1] performs [boss, sign-letter] pass [secretary-1, print-letter, secretary-2] performs [secretary-2, print-letter] pass [secretary-1, stamp-letter, secretary-2] pass [secretary-2, stamp-letter, secretary-3] performs [secretary-3, stamp-letter] combines [certify-letter, stamp-letter, sign-letter] combines [send-letter, certify-letter, print-letter] combines [write-letter, send-letter, type-letter-in-english]

22 Big example. Solution

23 Summing up… two views We have different views on the problem  Cooperation in multi-agent communities (strategic games)  Analyzing requirements These views might be though as different application areas of the proposed solution

24 Summing up… or what we do not have We need iterative solution building (iteration by imposing constraints on next solution) We need “partial” solution (compromise or equilibrium) and its evaluation We need the possibility of introducing new actors during the solution building

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