1. Designing Agent Societies
Volha Bryl
PhD student
ICT, DIT

2. Agent Society + collaboration (through delegation) - competitive goals…
- competitive goals
Agent …
Goals
Capabilities
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 PLANNING Let’s look at 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 are propagated through the graph and then eliminated – become done
Decomposes (A, G, G1, G2)
wants (A, G)
wants (A, G1)
wants (A, G2)

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

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

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

18. Example. Using the tool

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

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

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