By Scott A. DeLoach (auth.), Robin Cohen, Bruce Spencer (eds.)
The AI convention sequence is the finest occasion backed by means of the Canadian - ciety for the Computational reviews of Intelligence / Soci´et´e canadienne pour l’´etude d’intelligence par ordinateur. Attendees get pleasure from our quite often Canadian - mosphere –hospitable and stimulating. The Canadian AI convention showcases the wonderful learn paintings performed via Canadians, their foreign colleagues, and others identifying to affix us every one spring. foreign participation is often excessive; this 12 months virtually forty% of the submitted papers have been from non-Canadian - searchers. We accredited 24 papers and eight poster papers from fifty two full-length papers submitted. We additionally authorised 8 of ten abstracts submitted to the Graduate pupil Symposium. All of those approved papers look during this quantity. The Canadian AI convention is the oldest continuously-held nationwide AI c- ference on the planet. (ECCAI’s predecessor, AISB, held conferences in 1974, yet those have considering turn into international.) meetings were held biennially due to the fact that 1976, and every year for the reason that 2000. AI 2002 back joined its sister Canadian desktop technological know-how meetings, imaginative and prescient Interface and pix Interface, enri- ing the event for all individuals. The joint assembly permits us to stick - shaped approximately different components, to make new contacts, and maybe to enquire cross-disciplinary examine. This 12 months the meetings was once hung on the attractive campus of the college of Calgary, and lots of individuals took the chance to journey close by Ban? and the magni?cent Rocky Mountains.
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Additional info for Advances in Artificial Intelligence: 15th Conference of the Canadian Society for Computational Studies of Intelligence, AI 2002 Calgary, Canada, May 27–29, 2002 Proceedings
The underlying mechanism that allows agents to do business with one another in our marketplace is actually a form of the contract-net protocol [2,11], where buyers announce their desire for goods to all sellers via multicast or possibly broadcast. , the number of communicating agents and the number of desired goods) increases, this may run into diﬃculties due to the slow and expensive communication. The proposed buying algorithm provides a potential solution to this problem: A buyer may just send announcements of its desire for goods to its reputable sellers instead of all sellers, and thus reducing the communication load and increasing the overall system performance.
The main advantage of Kasbah is that its agents are autonomous in making decisions, thus freeing users from having to ﬁnd and negotiate with buyers and sellers. However, as admitted in , Kasbah’s agents are not very smart as they do not make use of any AI learning techniques. Vidal and Durfee  address the problem of how buying and selling agents should behave in an information economy such as the University of Michigan Digital Library. They divide agents into classes corresponding to the agents’ capabilities of modeling other agents: Zero-level agents are the agents that learn from the observations they make about their environment, and from any environmental rewards they receive.
Seller s will choose a price pˆ greater than or equal to cost cs (g, b) to sell good g to buyer b such that its expected proﬁt is maximized: pˆ = arg max p∈P p ≥ cs (g, b) hs (g, p, b), (9) where in this case arg is an operator such that arg hs (g, p, b) returns p. The expected proﬁt function hs is learned incrementally using reinforcement learning: hs (g, p, b) ← hs (g, p, b) + α(P rof its (g, p, b) − hs (g, p, b)), (10) where P rof its (g, p, b) is the actual proﬁt of seller s if it sells good g at price p to buyer b.
Advances in Artificial Intelligence: 15th Conference of the Canadian Society for Computational Studies of Intelligence, AI 2002 Calgary, Canada, May 27–29, 2002 Proceedings by Scott A. DeLoach (auth.), Robin Cohen, Bruce Spencer (eds.)