Don't you just love that light bulb moment? You know what I mean: There you are, sitting at your desk for days on end trying to crack a problem or generate some great idea, without success, and then, when you are completely detached and least expect it, from a source unimaginable... Eureka! I am sure we have all experienced it at some point or another. Evan Williams, the founder of Blogger and Twitter, certainly has. I read a nice article earlier today about how he stumbled upon his successes and the following three insights: "First, that genuinely new ideas are, well, accidentally stumbled upon rather than sought out; second, that new ideas are by definition hard to explain to others, because words can express only what is already known; and third, that good ideas seem obvious in retrospect."
Check out the article, entitled 'The accidental innovator', which featured in the December 22nd 2007 issue of 'The Economist'. It is a nice read.
Thursday, 3 January 2008
Saturday, 29 December 2007
European Workshop on Multi-Agent Systems
Quick update to say that I participated in the Fifth European Workshop on Multi-Agent Systems (EUMAS 07) earlier this month, which took place in Hammamet, Tunisia.
A great first-time experience, every step of the way: from writing the paper (Bilateral Agent Negotiation with Information-Seeking) and getting it reviewed to presenting and discussing it with those unfamiliar with my work. To add, it was really beneficial listening in and getting a feel for other ongoing research in the field of Multi-Agent Systems, especially that which is still in the early preliminary stages, like mine.
A great first-time experience, every step of the way: from writing the paper (Bilateral Agent Negotiation with Information-Seeking) and getting it reviewed to presenting and discussing it with those unfamiliar with my work. To add, it was really beneficial listening in and getting a feel for other ongoing research in the field of Multi-Agent Systems, especially that which is still in the early preliminary stages, like mine.
Tuesday, 4 December 2007
38, Agent Technology for e-Commerce
Contents of 'Agent Technology for e-Commerce' (2007), Maria Fasli
1, Introduction
(A paradigm shift; Electronic commerce; Agents and e-commerce)
2, Software Agents
(Characteristics; Agents as intentional systems; Making decisions; Planning; Learning; Architectures)
3, Multi-agent Systems
(Interaction; Agent communication; Ontologies; Cooperative problem-solving)
4, Shopping Agents
5, Middle Agents
6, Recommender Systems
7, Elements of Strategic Interaction
(Economics; Game Theory)
8, Negotiation I
(Protocols; Auctions)
9, Negotiation II
(Bargaining; Coalitions; Social choice problems; Argumentation)
10, Mechanism Design
11, Mobile Agents
12, Trust, Security and Legal Issues
(Trust; Electronic institutions; Reputation systems; Security; Cryptography)
1, Introduction
(A paradigm shift; Electronic commerce; Agents and e-commerce)
2, Software Agents
(Characteristics; Agents as intentional systems; Making decisions; Planning; Learning; Architectures)
3, Multi-agent Systems
(Interaction; Agent communication; Ontologies; Cooperative problem-solving)
4, Shopping Agents
5, Middle Agents
6, Recommender Systems
7, Elements of Strategic Interaction
(Economics; Game Theory)
8, Negotiation I
(Protocols; Auctions)
9, Negotiation II
(Bargaining; Coalitions; Social choice problems; Argumentation)
10, Mechanism Design
11, Mobile Agents
12, Trust, Security and Legal Issues
(Trust; Electronic institutions; Reputation systems; Security; Cryptography)
Monday, 26 November 2007
Intelligent Design
Source: The Economist, October 20th 2007
Section: Economics Focus
Title: Intelligent Design
Subtitle: A theory of an intelligently guided invisible hand wins the Nobel prize
... despite its dreary name, mechanism design is a hugely important area of economics, and underpins much of what dismal scientists do today. It goes to the heart of one of the biggest challenges in economics: how to arrange our economic interactions so that, when everyone behaves in a self-interested manner, the result is something we all like. The word "mechanism" refers to the institutions and the rules of the game that govern our economic activities...
Mechanism-design theory aims to give the invisible hand a helping hand, in particular by focusing on how to minimise the economic cost of "asymmetric information" - the problem of dealing with someone who knows more than you do...
His [Mr Hurwicz's] big idea was "incentive compatibility". The way to get as close as possible to the most efficient outcome is to design mechanisms in which everybody does best for themselves by sharing truthfully whatever private information they have that is asked for...
Section: Economics Focus
Title: Intelligent Design
Subtitle: A theory of an intelligently guided invisible hand wins the Nobel prize
... despite its dreary name, mechanism design is a hugely important area of economics, and underpins much of what dismal scientists do today. It goes to the heart of one of the biggest challenges in economics: how to arrange our economic interactions so that, when everyone behaves in a self-interested manner, the result is something we all like. The word "mechanism" refers to the institutions and the rules of the game that govern our economic activities...
Mechanism-design theory aims to give the invisible hand a helping hand, in particular by focusing on how to minimise the economic cost of "asymmetric information" - the problem of dealing with someone who knows more than you do...
His [Mr Hurwicz's] big idea was "incentive compatibility". The way to get as close as possible to the most efficient outcome is to design mechanisms in which everybody does best for themselves by sharing truthfully whatever private information they have that is asked for...
37, An implementation of norm-based agent negotiation
Notes taken from 'An implementation of norm-based agent negotiation' (2007), by Peter Dijkstra, Henry Prakken, Kees de Vey Mestdagh
1, Introduction
2, The Problem of Regulated Information Exchange
3, Requirements for the Multi-Agent Architecture
Knowledge: In order to regulate distributed information exchange, agents must have knowledge of the relevant regulations and the local interpretations of those regulations, their goals and the likely consequences of their actions...
Reasoning: ... the agents should be capable of generating and evaluating arguments for and against certain claims and they must be able to revise their beliefs as a result of the dialogues. Finally, in order to generate conditional offers, the agents should be able to do some form of hypothetical reasoning.
Communication: ...
4, Formalisation
Dialogical interaction: Communication language; Communication protocol
5, Agent Architecture
Description of the Components: User communication module; Database communication module; Agent communication language; Execution cycle module; Negotiation policy module; Argumentation system module
Negotiation Policy: ... Our negotiation policies cover two issues: the normative issue of whether accepting an offer is obligatory or forbidden, and the teleological issue whether accepting an offer violates the agent's own interests. Of course these policies can be different for the requesting and the responding agent... In the negotiation policy for a reject, the policy returns a why-reject move which starts an embedded persuasion dialogue. The specification and implementation of embedded persuasion dialogues will be the subject of future research.
Agent execution cycle: The agent execution cycle processes messages and triggers other modules during the selection of the appropriate dialogue moves. First, the speech act, locution and content are parsed from the incoming message, then depending on the locution (offer, accept, withdraw or reject) the next steps are taken... The execution cycle can be represented in Java pseudo-code...
6, Illustration of the Agent Architecture
Knowledge base: Knowledge is represented in the prolog-like syntax of the ASPIC tool...
Dialogue from example 2: ...
7, Conclusion
1, Introduction
2, The Problem of Regulated Information Exchange
3, Requirements for the Multi-Agent Architecture
Knowledge: In order to regulate distributed information exchange, agents must have knowledge of the relevant regulations and the local interpretations of those regulations, their goals and the likely consequences of their actions...
Reasoning: ... the agents should be capable of generating and evaluating arguments for and against certain claims and they must be able to revise their beliefs as a result of the dialogues. Finally, in order to generate conditional offers, the agents should be able to do some form of hypothetical reasoning.
Communication: ...
4, Formalisation
Dialogical interaction: Communication language; Communication protocol
5, Agent Architecture
Description of the Components: User communication module; Database communication module; Agent communication language; Execution cycle module; Negotiation policy module; Argumentation system module
Negotiation Policy: ... Our negotiation policies cover two issues: the normative issue of whether accepting an offer is obligatory or forbidden, and the teleological issue whether accepting an offer violates the agent's own interests. Of course these policies can be different for the requesting and the responding agent... In the negotiation policy for a reject, the policy returns a why-reject move which starts an embedded persuasion dialogue. The specification and implementation of embedded persuasion dialogues will be the subject of future research.
Agent execution cycle: The agent execution cycle processes messages and triggers other modules during the selection of the appropriate dialogue moves. First, the speech act, locution and content are parsed from the incoming message, then depending on the locution (offer, accept, withdraw or reject) the next steps are taken... The execution cycle can be represented in Java pseudo-code...
6, Illustration of the Agent Architecture
Knowledge base: Knowledge is represented in the prolog-like syntax of the ASPIC tool...
Dialogue from example 2: ...
7, Conclusion
Wednesday, 21 November 2007
36, Towards a multi-agent system for regulated information exchange in crime investigations
Notes taken from 'Towrds a multi-agent system for regulated information exchange in crime investigations' (2006), by Pieter Dijkstra, Floris Bex, Henry Prakken, Kees de Vey Mestdagh
1, Introduction
... we define dialogue policies for the individual agents, specifying their behaviour within a negotiation. Essentially, when deciding to accept or reject an offer or to make a counteroffer, an agent first reasons about the law and then about the interests that are at stake: he first determines whether it is obligatory or permitted to perform the actions specified in the offer; if permitted but not obligatory, the agent next determines whether it is in his interests to accept the offer...
2, The problem of regulated information exchange
3, Examples
4, Requirements for the multi-agent architecture
(Knowledge; Reasoning; Goals; Communication)
5, Outline of a computational architecture
Dialogical Interaction: communication language; communication protocol
The Agents: representation of knowledge and goals; reasoning engine; dialogue policies
6, Illustration of the proposed architecture
7, Conclusion
1, Introduction
... we define dialogue policies for the individual agents, specifying their behaviour within a negotiation. Essentially, when deciding to accept or reject an offer or to make a counteroffer, an agent first reasons about the law and then about the interests that are at stake: he first determines whether it is obligatory or permitted to perform the actions specified in the offer; if permitted but not obligatory, the agent next determines whether it is in his interests to accept the offer...
2, The problem of regulated information exchange
3, Examples
4, Requirements for the multi-agent architecture
(Knowledge; Reasoning; Goals; Communication)
5, Outline of a computational architecture
Dialogical Interaction: communication language; communication protocol
The Agents: representation of knowledge and goals; reasoning engine; dialogue policies
6, Illustration of the proposed architecture
7, Conclusion
Monday, 12 November 2007
Modelling Dialogue Types
Taken from 'Dialogue Frames in Agent Communication' (1998), by Chris Reed
Clearly the various types of dialogue are not concerned with identical substrate: persuasion, inquiry and information-seeking are epistemic, negotiation is concerned with what might generally be called 'contracts', and deliberation with 'plans'. The model presented [] does not aim to restrict either the agent architecture or the underlying communication protocol to any particular formalism...
Thus the foundation of the model is a set of agents, A, each of whom have a set of beliefs, B, contracts, C, and plans, P...
... it is possible to define the set of dialogue types, where each type is a name-substrate pair,
D = {(persuade,B), (negotiate,C), (inquire,B), (deliberate,P), (infoseek,B)}
From this matrix, a dialogue frame is defined as a tuple with four elements...
A dialogue frame is thus of a particular type, t, and focused on a particular topic, tau, - a persuasion dialogue will be focused on a particular belief, a negotiation on a contract, a deliberation on a plan, and so on. A dialogical frame is initiated by a propose-accept sequence, and terminates with a characteristic utterance indicating acceptance or concession to the topic on the part of one of the agents...
Clearly the various types of dialogue are not concerned with identical substrate: persuasion, inquiry and information-seeking are epistemic, negotiation is concerned with what might generally be called 'contracts', and deliberation with 'plans'. The model presented [] does not aim to restrict either the agent architecture or the underlying communication protocol to any particular formalism...
Thus the foundation of the model is a set of agents, A, each of whom have a set of beliefs, B, contracts, C, and plans, P...
... it is possible to define the set of dialogue types, where each type is a name-substrate pair,
D = {(persuade,B), (negotiate,C), (inquire,B), (deliberate,P), (infoseek,B)}
From this matrix, a dialogue frame is defined as a tuple with four elements...
A dialogue frame is thus of a particular type, t, and focused on a particular topic, tau, - a persuasion dialogue will be focused on a particular belief, a negotiation on a contract, a deliberation on a plan, and so on. A dialogical frame is initiated by a propose-accept sequence, and terminates with a characteristic utterance indicating acceptance or concession to the topic on the part of one of the agents...
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