A Geometric Semantics for Agent Interaction Protocols

1. A Geometric Semantics forAgent Interaction Protocols Peter McBurney Department of Computer Science University of Liverpool Liverpool L69 7ZF p.j.mcburney@csc.liv.ac.uk (Joint work with Simon Parsons, Brooklyn College, CUNY, New York.) Presentation to: Condensed Matter Physics Group Imperial College, London 29 October 2003

2. We are on the verge of a revolution . . . • Computational devices and systems will soon be: • Everywhere • Interconnected • Always active • Intelligent and autonomous. • Software systems will thus be: • Situated • Responsive to and influential upon their environment • Open • Computational entities will enter and leave these environments continually • Autonomous • Entities and systems will be goal-directed and exhibit autonomous behaviour • Systems and sub-systems will have multiple threads of control, not one. Agent Interaction Protocols

3. Autonomous intelligent software agents • It helps to conceive of computer systems as consisting of interacting autonomous entities. • A software agent is a computational entity with (some degree of): • Social awareness • Proactive behaviour towards defined goals • Reactive behaviour in response to its environment • Decision-making autonomy. (Wooldridge & Jennings 1995) • Some applications: • Air Traffic Control systems (agents representing aircraft and controllers) • Electronic commerce (agents representing buyers, sellers, others) • Management of utility networks (telecoms, electricity, etc) • Provisioning of complex products and services (e.g. telecoms services) • Management of fleets (vehicles, satellites, SCADA devices, etc). Agent Interaction Protocols

4. Two key research problems: • How to design agents • The most common approach is based on the Philosophy of Intention and Rational Agency (Bratman, Pollock) • e.g In the BDI model, agents are assumed have three types of mental states: Beliefs, Desires, and Intentions. • Considerable work has focused on formalizing these models using dialects of modal logic (epistemic, temporal, deontic, etc) or formalisms adopted from argumentation theory. • How to design Multi-Agent Systems (MAS) • How may agents interact with one another? • How may they make joint decisions? • I will consider agent interaction languages in this talk. Agent Interaction Protocols

5. How to humans interact? • By means of language • So, an obvious first step to designing agent interaction mechanisms is to consider the design of artificial languages for agent interaction. • Types of Agent Communications Languages: • Generic ACLs • Dialogue Game Protocols • Auction Mechanisms. • Following the philosophy of language, agent languages designers usually distinguish between two layers of communicated messages: • The topics of conversation (which may be represented in a suitable logical language) • eg “It is raining” • The illocutions which communicate something about these topics, eg • QUESTION(raining) • INFORM(raining) • DEMAND(raining). Agent Interaction Protocols

6. Generic ACLs Two major proposals: • USA DARPA’s Knowledge Query and Manipulation Language (KQML) • Arose from attempts to merge multiple knowledge bases • Focus was information-sharing between knowledgeable agents. • www.cs.umbc.edu/kqml/ • Foundation for Intelligent Physical Agents ACL (FIPA ACL) • Arose from an automated purchase transaction system at France Telecom • Focus was negotiation of tasks between expert agents • FIPA is a computer industry standards body for agent technologies. • www.fipa.org Agent Interaction Protocols

7. FIPA Agent Communications Language (FIPA ACL) • FIPA ACL has 22 illocutions • e.g. inform, query-if, request, agree, refuse. • Each has a defined syntax: (inform :sender (agent-identifier:name j) :receiver (agent-identifier:name i) :content “weather (today, raining)” :language Prolog) • The origins of FIPA ACL in knowledge-sharing and contract negotiations are apparent: • 11 of the 22 illocutions concern requests for or transmissions of information • 4 involve negotiation (e.g. cfp, propose, reject-proposal) • 6 involve performance of action (e.g. refuse, request) • 2 involve error-handling of messages (e.g. failure). Agent Interaction Protocols

8. Problems with FIPA ACL • The language implicitly assumes eternal connections between the agents • Where are the illocutions for entering and leaving dialogues? • Where are the illocutions for permitting or contesting participation? • As befits a language for knowledge-sharing, the semantics impose sincerity: • Agents cannot utter beliefs they do not hold. • As befits a language for contract negotiations, the underlying (implicit) argumentation theory is simplistic. • There are no illocutions for contesting statements, or for requesting or giving reasons for claims, or for structuring dialogue. • The participants incur no dialectical obligations. • The language does not readily support self-transformation • How may an agent express a change of its beliefs? • The absence of an explicit argumentation theory causes a state-space explosion: • Any illocution may follow any other: Disruptive behavior is not precluded. • Dialogue Game Protocols have been proposed as a solution to this problem. Agent Interaction Protocols

9. Dialogue Game Protocols • “Games” between two or more participants where each “moves” by making utterances, subject to some rules. • Origins in Philosophy • Aristotle and medieval philosophers • Revived for the study of supposedly fallacious reasoning (Hamblin 1970, MacKenzie 1979) • Proof theory for intuitionistic & classical logic (Lorenzen 1959) • Applied to quantum physics (Mittelstaedt 1979). • Within computer science, applied to: • Modeling human dialogues in computational linguistics • Software development processes • Modeling legal reasoning • Man-machine dialogues (e.g. for automated tutoring systems) • Protocols for agent dialogues. Agent Interaction Protocols

10. A DG Protocol is defined in terms of: • A language of statements (the topics of the dialogue) • Usually expressed in some logical language (e.g. propositional logic, FOL, etc). • A set of illocutions instantiated with the statements • eg assert(p), accept(p), contest(p). • Combination rules, defining the circumstances in which each instantiated illocution may be uttered • eg It may not be possible to assert a statement and then its negation. • Termination Rules, defining the circumstances in which dialogues terminate. • Rules for creating and combining commitments • Commitment Stores: publicly-accessible sets of statements, holding the commitments incurred by participants. • Dialogic and external (semantic) commitments, and rules for their combination. Agent Interaction Protocols

11. An influential typology of dialogues Doug Walton and Erik Krabbe (1995) have proposed a typology of human dialogues, based on: the information known to participants at commencement; their respective objectives; and the purpose(s) of the dialogue. • Information-seeking dialogues • One participant seeks the answer to a question which it believes another knows. • Inquiry dialogues • All participants collaborate to find the answer to a question which no one knows. • Persuasion dialogues • One participant seeks to persuade other(s) to endorse a statement. • Negotiation dialogues • Participants seek to divide a scarce resource. • Deliberation dialogues • Participants collaborate to decide a course of action in some situation. • Eristic dialogues • Participants quarrel to vent perceived grievances, as a substitute for physical fighting. Agent Interaction Protocols

12. Formal Dialogue-Game Protocols • Agent interaction protocols have been designed for: • Inquiry dialogues (McBurney & Parsons 2001) • Persuasion dialogues (Dignum, Dunin-Keplicz & Verbrugge2000) • Negotiation dialogues (Amgoud, Parsons & Maudet 2000; Sadri, Toni & Torroni 2001; McBurney, van Eijk, Parsons & Amgoud 2003) • Deliberation dialogues (Hitchcock, McBurney & Parsons 2001). • These protocols are more constrained than are generic Agent Communications Languages • Rules govern combinations of locutions: agents usually cannot say just anything at anytime. • Usually, the protocol is designed with a specific purpose in mind, and informed by an explicit theory of argument. Agent Interaction Protocols

13. Example locutions in a Dialogue Game Protocol Locutions for a deliberation dialogue (to jointly decide a course of action): • open_dialogue(Pi, q?) • enter_dialogue(Pj, q?) • propose(Pi, type, t) • assert(Pi, type, t) • prefer(Pi, a, b) • ask_justify(Pj, Pi, type, t) • move(Pi, action, a) • retract(Pi, locution) • withdraw_dialogue(Pi,q?) where: • Pi, Pj are participating agents • type  {question, goal, constraint, perspective, fact, action, evaluation} • and there are various constraints on, and impacts of, utterance of these locutions. (Hitchcock, McBurney & Parsons 2001) Agent Interaction Protocols

14. Example (continued) • For this protocol, the purpose is joint practical reasoning: • For a group of participants to jointly decide on an action, or course of action, in some situation • Or, at least, to decide if they have a joint responsibility for such a decision. • The theory of argument made explicit was Harald Wohlrapp’s retroflexive argumentationmodel (1998) • Here, proposed actions and suggested justifications are both modified iteratively, in the light of reflections on each. • For example: • The law should allow euthanasia, since this would permit people in terminal pain to die. • But such a law could be abused by (say) evil doctors or relatives. • Thus the law should allow euthanasia only under some conditions, for example, that two independent doctors agree. • Etc. Agent Interaction Protocols

15. Auction mechanisms • The simplest communications protocols are the mechanisms of commerce: • Auction mechanisms • Mechanisms for negotiations • Cake-cutting algorithms, etc. • Called “Game-Theoretic Mechanisms” in AI. • At the simplest, these involve illocutions for: • Proposing a deal (a division of some scarce resource) • Accepting or rejecting a proposed deal • (And possibly also) Entering and leaving the interaction. • Because of the rise of e-commerce, these mechanisms have been much studied within Computer Science/AI of late. • See “Agent-Mediated e-Commerce” Workshop series (Springer). Agent Interaction Protocols

16. Examples of GT protocols • Auction Mechanisms • English (ascending) auctions • Dutch (descending) auctions • Vickrey (second-price) auctions. • Combinatorial auctions • Bidders may bid on any combination of a set of items. • Continuous Double Auctions (k-CDA) • Multiple buyers and sellers make bids and asks (respectively) • Transaction price is a function (with parameter k) of bid and ask prices • Used in most organized stock and commodity exchanges. • Monotonic Concession Protocol • 2+ participants • Participants may propose (make an offer), counter-propose, accept a proposal, or withdraw. • Proposals must always concede, relative to previous proposals. Agent Interaction Protocols

17. Relationship between types of interaction protocols • Generic ACLs Dialogue Game Theoretic • Game (Auction) • Protocols Mechanisms Increasing expressiveness Increasing constraints on utterances Agent Interaction Protocols

18. Key Research Challenges • Defining the philosophies underlying agent societies • e.g. Argumentation theories; philosophies of democracy; etc. • Automation of Inquiry, Deliberation and Command dialogues • We have defined protocols for the conduct of these dialogues. • Key challenge: How are possible hypotheses/action-options generated? • Developing a formal, mathematical theory of interaction protocols • To understand the space of protocols in its entirety, and to understand the relationship between two or more protocols. • Currently under development • Johnson, McBurney & Parsons • Drawing on Category Theory and Algebraic Topology. • Understanding the relationships between local and global properties • How to achieve dialogue-level properties (e.g. fast termination) using only local levers (e.g. locution-combination rules)? Agent Interaction Protocols

19. Semantics for ACLs • Linguistic theory distinguishes between: • Syntax of a language: its words, phrases, sentences and grammar • Semantics of a language: what meanings are assigned to the words, phrases & sentences • Pragmatics of a language: how the words, phrases and sentences and are used in conversation. • Within mathematical logic, the Wittgenstein-Tarskian view of semantics is as a mapping from the legal formulae or sentences of a logical language to truth-values. • Truth Values may be viewed as mathematical objects, eg: {0,1}. • Model Theory studies the objects which are semantics for logical languages and their relationships to one another, as abstract mathematical objects. • In Theoretical Computer Science, there are several types of semantics: • Axiomatic • Operational • Denotational • Game-Theoretic. Agent Interaction Protocols

20. Semantics of ACLs • Considerable work on defining semantics of individual utterances • Less work on semantics of dialogues under a given protocol • No work yet on semantics of protocols • My work is intended to develop a formal semantics of protocols • To be able to determine if two protocols are the same or not • To understand the relationship between syntactic form of a protocol and the properties of the dialogues conducted under it. • This relationship is not continuous. Agent Interaction Protocols

21. Axiomatic Semantics • An axiomatic semantics articulates the pre-conditions and post-conditions of an utterance • The semantics define the pre-conditions required for an utterance to be validly made, and the post-conditions which occur upon its utterance. • This is usually done in a formal logical language, such as First-Order Logic. • FIPA ACL has been given a formal, axiomatic semantics using speech act theory from the philosophy of language. • Speech acts are utterances which are intended to change the world in some way. • “I name this ship, The Queen Elizabeth.” • “I declare you man and wife.” • Austin 1955, Searle 1969. • The speech act semantics for FIPA ACL links utterances to the private mental states of the participants. • Their Beliefs, Uncertain Beliefs, and Intentions. • This semantics has been formalized using modal epistemic logic. • Bretier, Cohen, Levesque, Perrault, Sadek (1979, 1990, 1997). Agent Interaction Protocols

22. For example: inform • Suppose agent A informs agent B that “It is raining”. • Required Pre-conditions: Before a valid utterance by A: • A must believe “It is raining”, • A must not already believe that B has any belief regarding whether or not it is raining (i.e. A must believe that B has an uncertain belief about this matter) and • A must desire that B also comes to believe “It is raining”. • Post-conditions: Upon receipt by B of such an utterance by A: • B must believe that A believes “It is raining” and • B must believe that A desires that B believes “It is raining”. • Note that following the utterance by A, B may or may not adopt the belief “It is raining”. Agent Interaction Protocols

23. Operational Semantics • An operational semantics treats the utterances in an agent interaction as programming commands on some large, virtual machine • The commands acts to change the state of this virtual machine. • We can therefore view the utterances as functions which cause state transitions. • From a formal axiomatic semantics we can define an operational semantics, which indicates the state transitions for every possible utterance. • Does the virtual machine include the mental states of the interacting agents? • An operational semantics has been defined for a dialogue game protocol for consumer purchase negotiations. • McBurney, van Eijk, Parsons & Amgoud 2003. Prior state of machine Utterance Subsequent state of machine Agent Interaction Protocols

24. Game Semantics • To each formulae in a language is associated a game • Usually between 2 imaginary players: Proponent & Opponent • A formula is considered to be true iff a designated player (usually Proponent) has a winning strategy in the associated game. • Example: Ehrenfreucht-Fraisse games • To assess whether two collections of objects are isomorphic, allow each player to select objects in turn. • One player seeks to show the objects selected are in 1:1 relationship, the other player that this is not so. • Used in model theory, and also recently in theoretical computer science to give a semantics for some programming languages. Agent Interaction Protocols

25. Denotational Semantics • Each formulae is mapped to some object in a mathematical space • E.g. Mapping logical formulae to the set {True, False} or {0,1}. • The standard semantics for modal logic languages is the Possible Worlds semantics • Due to Leibniz, Kanger (1957), Kripke (1959/1962), Hintikka (1962) (and Everett 1957) • This is a collection of states of the world, at each of which some propositions are true and some not. • Some worlds are connected by accessibility relationships, indicating (for example) that it is possible to move from one world-state to another. Agent Interaction Protocols

26. Negotiation and Deliberation • Deliberation Dialogues are dialogues over possible actions (or courses of action) • Negotiation dialogues are a special case of Deliberations, where the actions are intended to divide some scarce resource. • Deliberations typically involve one or more participants making proposals for action, which all parties then consider. • We assume that the interaction protocol enables participants to: • Suggest proposals for action • Accept or reject proposals which have been suggested • Express a preference between two suggested proposals • Commit to execute a specific proposal. • We also assume that time is represented by a set common to all participants which is countable, and that exactly one utterance occurs at each time-point. Agent Interaction Protocols

27. A category-theoretic semantics • At each time point t: • We specify a proto-category representing the public utterances in the dialogue up to that time • Called the Dialogue (or Public) Store • Objects: Proposed actions • Arrows: Expressed preferences between actions. • We specify a proto-category for each participant • Called the Private Store of the Participant • Objects: Possible actions under consideration by the Participant • Arrows: Determined preferences between actions • One distinguished object: ND (“No Deal”), representing termination of the deliberation without an agreement on an action being reached. • For these entities to be categories, the participants’ preferences must be transitive. Agent Interaction Protocols

28. ND ND A D B F E C F A B A E C D D G Private Store: Participant 1 Private Store: Participant 2 Dialogue (Public) Store Time t > 8 Agent Interaction Protocols

29. Current Work • Formalize this semantics, and study the mathematical properties of these structures. • Not much work in CT on linked sequences of categories. • Represent common deliberation and negotiation protocols in this way. • Identify categorical constructs analogous to decision-mechanisms in deliberations and negotiations • Decisions internal to the participants • Judgment aggregation decisions in the dialogue (eg voting). Agent Interaction Protocols

30. Further reading: • Agent-Enabled Computing • M. Luck, P. McBurney and C. Preist (2003): Agent Technology: Enabling Next Generation Computing. AgentLink II Network of Excellence. • Available from: www.agentlink.org • M. J. Wooldridge (2002): Introduction to Multi-Agent Systems (Wiley) • M. J. Wooldridge (2000): Reasoning About Rational Agents (MIT Press). • Game-theoretic Interaction Mechanisms: • J. S. Rosenschein & G. Zlotkin (1994): Rules of Encounter (MIT Press) • S. Kraus (2001): Strategic Negotiation in Multiagent Environments (MIT Press). • Agent Communications Languages and Dialogue Game Protocols: • www.fipa.org • www.cs.umbc.edu/kqml/ • M-P. Huget (Editor) (2003): Communication in Multi-Agent Systems: Agent Communication Languages and Conversation Policies. (Springer, LNAI 2650). • F. Dignum (Editor) (2003): Advances in Agent Communication. (Springer LNAI 2922) (forthcoming). Agent Interaction Protocols

31. Finally . . . Thank you for inviting me and for listening! Agent Interaction Protocols

32. Combining dialogues of different types • Most real human dialogues are complex combinations of primary types • e.g. Analysis of environmental risk of new technologies involves combinations of Information-seeking, Information-Provision, Inquiry, Persuasion, Negotiation, Deliberation, Command, and even Eristic dialogues. • There are two proposals for formalisms to represent combinations of agent dialogues: • Reed’s Dialogue Frames (1998) can represent iterated, sequential & embedded dialogues. • This formalism is neutral regarding the syntax used in each dialogue. • McBurney & Parsons ADF (2002) can represent iterated, sequential, parallel & embedded dialogues. • This formalism is a dialect of Dynamic Modal Logic, and is potentially generative, i.e. it can be used generate many types of dialogues automatically. • Both formalisms permit the incorporation of new primary types of dialogues. Agent Interaction Protocols

33. Semantic Verification Problem: How to verify that an agent using an ACL conforms to the (private) semantics of that ACL? • i.e. How to verify that an agent really believes (or prefers or intends) what it says it does? Proposed Partial Solutions: • Social Semantics (Singh) • Have agents profess their beliefs and intentions publicly • Then check their subsequent utterances for consistency against these professions. • Semantic Contestability (McBurney & Parsons) • Allow participants to question and contest each other’s statements • Require agents to provide justifications for assertions (of beliefs, preferences, intentions) and allow argument over these justifications • There is a connection here with the verificationist theory of truth of Michael Dummett and Crispin Wright. Agent Interaction Protocols

34. Automation of ACL dialogues Agent interactions to jointly decide use of shared resources have used: • Theories of Persuasion • Adopted from psychology (Abelson 1960, 1970): • Example: Sierra, Jennings, Noriega & Parsons 1998. • Agents offer threats/rewards to persuade others to adopt proposals • Acceptance/rejection based on relative positions in a social hierarchy. • Argumentation Theory • Parsons, Sierra & Jennings 1998. • An agent generates a proposal by constructing an argument (a tentative proof) for an intention it has, and communicating this to the other participants. • The other agents attempt to counter this argument, and only accept it if they fail to counter it. • Uses the Logic of Argumentation of Cancer Research UK. Agent Interaction Protocols

35. Automation of DG dialogues (1) • Negotiation dialogue protocol of Amgoud, Parsons & Maudet 2000 • 7 Locutions: assert, accept, question, challenge, request, promise, refuse. • Locutions may be instantiated with propositions and arguments for propositions. • Agents vested with an argumentation mechanism, to generate arguments for propositions and to accept or reject arguments received from other agents. • Not quite automatic. • Negotiation dialogue protocol of Sadri, Toni & Torroni 2001. • Based on Amgoud, Parsons and Maudet 2000. • 6 Locutions: accept, challenge, request, promise, refuse, justify. • Agents co-operate to agree the use of possibly-scarce resources. • Agents vested with abductive logic mechanisms (if-then rules). • These determine which locution should next be uttered, based on the most recent locution uttered and the current status of the agent’s resources knowledge base. • No theoretical grounding for these if-then rules. Agent Interaction Protocols

36. Automation of DG dialogues (2) • A Consumer Purchase Transaction Protocol • A protocol for purchase negotiations for consumer durables, based on a standard decision model from marketing theory (Roberts & Lilien 1993). • 11 illocutions: • open_dialogue • enter_dialogue • seek_info • willing_to_sell • desire_to_buy • prefer • refuse_to_buy • refuse_to_sell • agree_to_buy • agree_to_sell • withdraw_dialogue. Agent Interaction Protocols

37. Automation of DG dialogues (2) (continued) • Based on the marketing theory decision model, we have defined semantic decision mechanisms for the participating agents, e.g. • Seek_Information • Provide_Information • Assess_Options, etc. • Agents vested with these decision mechanisms and using the protocol may engage in automated dialogues. • This is proven by defining an Operational Semantics for the protocol, a formal definition of the locutions in terms of their effects on the interaction state-space. • Protocol due to: • McBurney, van Eijk, Parsons & Amgoud 2003. Agent Interaction Protocols