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Outline
 Software agents
 Agent Communication Languages (ACLs)
 Syntax of ACLs
 Semantics of ACLs
 Dialog Game Protocols
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Software Agents

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
• Entities will enter & leave these environments continually
– Autonomous
• Entities and systems will be goal-directed and exhibit autonomous behaviours
• Systems and sub-systems will have multiple threads of control.
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Implications for software engineering
A revolution will be needed for software engineering:
 Robust Systems
– Robust to: changes in their environment, new entities, new
relationships between entities, new goals, etc.
– Designing for system-level properties:
• Engineers need to generate desired system behaviours without designing all the components, and without knowledge of all the initial states and possible interactions.
– Living Systems
• Systems need to be tested, maintained and upgraded without removal, or even without downtime.
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Implications for software engineering
 Software engineering starts to resemble:
– Economic mechanism design (the design of marketplaces)
– Ecology and ecosystem management
– Statistical physics.
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Reminder: Autonomous intelligent software agents
It helps to conceive of computer systems as consisting of interacting autonomous entities (“agents”).
 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)
 Agents v. Objects (Object-Oriented Programming)
– Agents are autonomous (they are requested to act, not invoked)
– A multi-agent system (MAS) has multiple, interacting threads of control, not one.
– Agents have dynamic relationships with each other, not static.
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Some applications
 Air Traffic Control systems – aircraft and controllers
 E-commerce
– buyers, sellers, auctioneers
 Provisioning of complex products and services – eg, telecommunications services
 Logistics and management of fleets
– vehicles, satellites, sensor networks, drones, etc.
 Conceptualization of distributed software systems.
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Agents direct the second economy
 Parallel to the physical economy, we now have a second economy
– Digital, Internet-enabled
– With machine-to-machine communications
 The second economy increasingly relies on interacting software entities, which are
– Intelligent
– Autonomous
– Dynamic
– Able to learn
– Self-organizing.
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Two key agendas:
 How best to architect (design and create) agents
– The most common approach is based on the Philosophy of Intention and Rational Agency (Bratman, Pollock)
• Eg, 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).
 How best to architect Multi-Agent Systems (MAS)
– How may agents interact with one another?
– How may they make collaborate or compete, or make joint decisions?
– How to ensure desired system properties when other programmers design the entities involved?
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Human Language

Human language has many functions
 A means of information transfer
– The weather is sunny today.
– I am hungry.
– I prefer chicken to fish.
– I intend to eat lunch.
 A means of co-ordinating joint actions
– Would you be free for lunch today?
– We can divide the bill equally.
 A means of establishing and maintaining social relationships
– Let’s do lunch!
 A signalling system
– Let me pay for lunch!
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Aspects of human languages
Linguistic theory distinguishes:
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 are used in conversation.
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A typology of human utterances
 Factual statements (Propositions)
– Purport to describe states of the real-world
 Expressive statements
– Purport to describe internal mental states of speaker
 Social Connection statements
– Purport to describe social relations between participants or others
 Commissives
– Speaker desires a particular world state, and proposes actions to establish or
maintain this world state
 Directives
– Speaker desires a particular world state, and seeks to direct others to
undertake actions to establish or maintain this world state
 Inferences
– Statements which draw logical inferences from earlier statements
 Argumentation statements
– Statements which question, challenge or justify earlier statements
 Control statements
– Statements which refer to the dialog itself, aiming to facilitate communication.
McBurney & Parsons 2004, drawing on Austin, Searle, Habermas.
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Not all utterances are propositions
Speech Act Theory in the Philosophy of Language is an account of these other utterances
 This theory is due to:
– (1710–1796)
– (1883–1917)
– (1911–1960)
– (1932– )
– (1929– )
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Speech acts
 Some statements change the world
by their very utterance, eg.
– “I name this ship, The Queen Elizabeth.”
– “I declare you man and wife.”
 These statements perform some action, but only under certain pre-conditions:
– eg, For a marriage declaration to be legally binding in the UK, the celebrant must be registered, the location must be a registered location, both the individuals must be single, at least two witnesses must be present, etc.
 Speech acts can be defined in terms of their felicity conditions and their rational effects.
– Modern theory due to: Austin 1955, Searle 1969.
 Applications to linguistics, social sciences, computer science. Machine Languages 16

Aside: Shannon’s communication theory
 developed an influential theory of communication in the 1930s and 1940s
– Widely used in the design of electronic communications systems
 But: Shannon explicitly ignored the semantics of messages – This is inappropriate for agent-to-agent communications
 Example:
– I promise you to wash the car. vs.
– I command you to wash the car.
Syntactically, there is no difference between these two statements, but they have very different meanings and implications.
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Agent Communications Languages

What are Agent Communication Languages?
A means of communications (as with human languages)
– between independent, autonomous entities
Functions: information transfer, action co-ordination, social manipulation, signalling.
Programming languages for agents
– To enable software entities to achieve their goals • eg, to communicate with other agents
– We desire that agent communication can be automated
Software engineering methods
– To enable software engineers to achieve their goals • eg, for their agents to interact with other agents
– We desire that the level of abstraction facilitate the S/E task
Formal languages
– Defined syntax
– Defined semantics
– We desire that properties be known and understood before deployment.
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So we draw upon:
 Linguistic theory
 The philosophy of language
 The philosophy of communicative action
 The theory of semiotics (signs and signalling)
 Social anthropology
 The theory of programming languages
 Software engineering theory
 Formal logic.
Note that the word “semantics” has different meanings in these different fields.
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Agent Communication Languages (ACLs)
 Two major proposals for ACLs:
– Knowledge Query and Manipulation Language (KQML)
– IEEE Foundation for Intelligent Physical Agents ACL (FIPA ACL)
 Both ACLs distinguish between two layers of communicated messages:
– The topics of conversation (which may be represented in a suitable logical language)
– The utterances which refer to these topics • For example:
– query (Is it raining?)
– inform (It is raining)
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FIPA Agent Communications Language
 IEEE FIPA ACL has 22 locutions (types of utterances)
– eg, 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 are in knowledge-sharing and automated contract negotiations.
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Classification of FIPA ACL locutions
 Factual statements:
 Expressive statements:
 Social connection statements:
 Commissives:
 Directives:
 Inferences:
 Argumentation statements:
 Control statements:
8 locutions (eg, confirm) 1 locution (inform)
1 locution (inform)
5 locutions (eg, propose) 5 locutions (eg, request) 1 locution (inform)
0 locutions
4 locutions
(eg, not-understood)
Conclusions:
– An absence of locutions supporting argumentation – An overloading of some locutions (eg, inform).
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Some flaws with FIPA ACL
 As befits a language for knowledge-sharing, the semantics impose sincerity
– For many applications, sincerity is not appropriate (eg, negotiations).
 As befits a language for contract negotiations, the underlying (implicit) argumentation theory is simplistic
– No ability to argue, to challenge or to justify statements.
 The absence of an explicit argumentation theory causes a state- space explosion
 The language does not readily support self-transformation
 The private axiomatic semantics is not verifiable.
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Semantics of
Agent Communications Languages

What are the purposes of an ACL semantics?
To ensure shared understanding of language in communication
– By agents
– By their human principals
– By the software developers of the MAS
– By the software developers of the participating agents
– By other stakeholders (eg, regulators).
To enable study of formal properties of the language, eg:
– Can dialogs always terminate?
– Can successful termination be achieved?
– What are the properties of outcome states?
– Can dialogs always continue?
To provide an account of what is happening when an ACL is used
– Eg, social semantics
To facilitate successful software engineering & implementation. Machine Languages 26

Semantics of ACLs
 Considerable work on defining semantics of individual utterances
 Less work on semantics of dialogues under a given protocol
 Very little work yet on semantics of protocols
 Types of semantics (from programming language theory): – Axiomatic
– Operational
– Game-theoretic – Denotational.
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Axiomatic Semantics
 An axiomatic semantics articulates the pre-conditions and post- conditions of an utterance
– What needs to be true beforehand and
– What becomes true aftterwards
 This is usually done in a formal logical language, such as First- Order Logic or modal logic.
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Semantics of FIPA ACL
 FIPA ACL has been given a formal, axiomatic semantics using speech act theory, called SL (“Semantic Language”)
 An axiomatic semantics articulates the pre-conditions and post- conditions of each utterance
 The speech act semantics SL for FIPA ACL links utterances to the private mental states of the participants
– Beliefs, Uncertain Beliefs, Desires, and Intentions
– This semantics has been formalized using modal epistemic logic.
Bretier, Cohen, Levesque, Perrault, Sadek (1979, 1990, 1997)
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For example: inform
 Suppose agent Alice (A) informs agent Bob (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 a belief regarding whether or not it is raining
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”.
 Following the utterance by A, B may or may not adopt the belief “It is raining”.
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The FIPA semantics for inform
 The single most common computer interaction is a request for a
password.
– System S asks agent A to enter a password to login into system S
 Can A use the inform utterance to give the password? – inform (A, S, password= pword263)
 Three pre-conditions:
– A must believe “password=pword263”. YES
– A must not already believe that S has a belief regarding whether or not “password=pword263”.
But S already knows the password, and A knows that S knows the password.
and
– A must desire that S also comes to believe “password=pword263”. But what does A care about the future beliefs of S?
 So an agent compliant with the semantics of FIPA ACL could not validly use the inform utterance to provide a password.
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Moreover . . .
Suppose Alice tells you that some proposition P is true. What can you conclude from this fact?
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Some possible conclusions
 That P is true.
 That Alice believes that P is true.
 That Alice wants you to believe that P is true.
 That Alice wants you to believe that she wants you to believe that P is true.
 That Alice wants you to NOT believe that P is true.
 That Alice wants you believe that she wants you to not believe
that P is true.
 That Alice wants you to believe that P is not true.
 That Alice wants you to believe that she wants you to believe that P is not true.
 …
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Operational Semantics
 An operational semantics treats the utterances in an agent interaction as programming commands working on some large, virtual machine
– The commands acts to change the state of this virtual machine.
 We can therefore view utterances as functions which cause state transitions.
 Does the virtual machine include the mental states of the interacting agents?
Prior state Utterance of machine
Machine Languages
Subsequent state of machine
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Denotational Semantics
 Each formula is mapped to some object in a mathematical space
 Having a denotational mapping means we can reason about the
language by reasoning about the mathematical objects.
 Examples:
– Possible Worlds Semantics
– Game Semantics
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Possible Worlds Semantics
 The standard semantics for modal logic languages is the Possible Worlds semantics
– 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.
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Game Theoretic Semantics
 Each well-formed statement in the language corresponds to a game G, usually between two fictional players, Protagonist P vs. Antagonist A.
 Usually, we say that the goals of the players are:
– PaimstowinthegameG,and
– A aims is to prevent P from winning the game G.
 The statement is true (or valid) if and only if P always has a winning strategy for the game.
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Semantics of ACLs
 ACLs and protocols usually defined with an axiomatic semantics for the utterances
 Some protocols have been given an operational semantics
– Does an operational semantics have meaning in an open distributed system, when any encompassing machine is entirely virtual?
 In a handful of cases, a denotational semantics has been given for utterances in a protocol.
– For example: utterances conceived as actions on a tuple space.
– Research is still immature.
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Dialog Game Protocols

FIPA ACL’s lack of structure
Problem: Lack of structure, state-space explosion.
Possible Solutions:
 Conversation Policies (CPs)
– Sequences of utterance-patterns for a small number of
utterances
• Eg, a question must be followed by a response
• Eg, a request for proposals must only be followed by a proposal or proposals.
 Formal Dialog Games (DGs).
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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 the logical fallacies in 1960s
– Applied to quantum physics (Mittelstaedt 1979).
 Within computer science, applied to protocols for automated agent dialogues.
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A DG Protocol is defined in terms of:
 A language of statements (the topics of the dialog)
 A set of utterance types instantiated with the statements
– e.g. assert(p), accept(p), contest(p).
 Combination rules, defining the circumstances in which each
instantiated utterance may be uttered
 Termination Rules, defining the circumstances in which dialogs terminate.
 Rules for creating and combining commitments
– Commitment Stores: publicly-accessible sets of statements,
holding the commitments incurred by participants.
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Relationship between types of interaction protocols
Generic ACLs
Dialogue Game Protocols
Auction Mechanisms
Increasing expressiveness
Increasing constraints on utterances
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An influential typology of dialogues
Classification on the basis of what each participant knows at outset, and what they each aim to achieve in the dialog.
 Information-seeking dialogues
 Inquiry dialogues
 Persuasion dialogues
 Negotiation dialogues
 Deliberation dialogues
 Eristic dialogues.
Walton and Krabbe (1995)
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Aside: HTTP
 What types of dialogs does Hyper-Text Transfer Protocol enable?
 GET
– One agent (the client) requests another agent (the server) to transfer from server to client a copy of the object specified by URL.
– Server responds by doing so, or by sending a message explaining why server cannot do so.
• eg, 404 Error: File Not Found
• eg, 503 Error: Service Unavailable
 PUT, POST
– One agent (the client) transfers some data to another agent (the server).
 HTTP combines dialogs for: – Action-requests
– Information-provision
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Formal Dialogue-Game Protocols
 Agent DG protocols have been designed for all the Walton and Krabbe types, as well as:
– Information-provision dialogs
– Argumentation dialogs
– Command dialogs
– Discovery dialogs
– Design dialogs
 These protocols are more constrained than are generic Agent Communications Languages
– Rules govern combinations of locutions: agents usually cannot just say anything at any time.
– Usually, the protocol is designed with a specific purpose in mind, and design may be informed by an explicit theory of argument.
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A simple DG protocol for info-seeking
 Information-Seeking dialog
– Parsons, Wooldridge & Amgoud (2002).
 For p a proposition, and S a set of propositions:
 Valid utterances: – question(p)
– assert(p) assert(S) – accept(p) accept(S) – challenge(p)
 Plus: special argument U for assert(.) to indicate that speaker is unable to give a response.
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Information-seeking dialogue (2)
 Just two agents, A and B.
Valid combination rules are given by:
1. A:
2. B: –
–
–
3. A: – – –
question(p)
Responds with one of:
assert(p) assert(~p) assert(U)
Responds with one of (respectively): accept(p) v challenge(p)
accept(~p) v challenge(~p) DIALOGUE ENDS
4. If accept(.), then DIALOGUE ENDS.
5. B: Replies to challenge with:
– assert(S) (S an argument for p or ~p) 6. Goto3.
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Example Application: BGP
 The Border Gateway Protocol (BGP) is an Internet Protocol at Layer 3 (the Network Layer)
– Allows for negotiation between neighbouring autonomous domains over routing and reachability of internet addresses.
 The Fatio Argumentation Protocol is an extension to FIPA ACL to allow intelligent agents to argue with one another.
– Allows for claims to be questioned & challenged, and for claims to be justified.
 Fatio has been used to support automated identification and resolution of conflicts between hosts using the BGP.
McBurney & Parsons (2004) Kodeswaran, Perich, Li, Joshi & Finin (2010)
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Research Challenges
 Dialogs over action
 Semantics of protocols
 Properties of protocols
 Better understanding of the relationships between syntax rules and protocol properties
 How best to organize libraries of protocols (for efficient storage and search)
 Automated negotiation over protocols.
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Thank you!