Staff

Speaker: Jie Zhang

In this talk, we consider the challenge of designing an electronic marketplace populated with buying and selling agents that learn to choose the best business partners, for their users. In particular, we present a novel mechanism that creates incentives for honesty in this electronic marketplace.

Speaker: Sandip Sen (University of Tulsa)

We believe that intelligent information agents will represent their users' interest in electronic marketplaces and other forums to trade, exchange, share, identify, and locate goods and services. Such information worlds will present unforeseen opportunities as well as challenges that can be best addressed by robust, self-sustaining agent communities.

Speaker: Russ Greiner (University of Alberta)

Researchers often use clinical trials to collect the data needed to evaluate some hypothesis, or produce a classifier. During this process, they have to pay the cost of performing each test.

Speaker: Julie Weber

This talk will describe two projects in the design of intelligent assistants. The first part will focus on a new algorithm for active learning that is embedded within an interactive calendar management system to learn users' scheduling preferences.

Speaker: Chun-hung Li (Professor at Hong Kong Baptist University)

In the first part of the talk, we will briefly go over our recent work on the modeling of user participation in online discussion forum.

Speaker: Xin Li (Hong Kong Baptist University)

Partially observable Markov decision process (POMDP) is a commonly adopted framework to model planning problems in a stochastic environment. However high dimensionality of POMDP's belief space is still one major cause for making the underlying optimal policy computation intractable.

Speaker: David Yeung
 

Speaker: Dana Wilkinson

In a variety of domains it is desirable to learn a representation of an environment defined by a stream of sensori-motor experience. In many cases such a representation is necessary as the observational data is too plentiful to be stored in a computationally feasible way.

Speaker: Paul Thagard

This talk proposes a theory of how conscious emotional experience is produced by the brain as the result of many interacting brain areas coordinated in working memory.

Using adaptive consultation of experts to improve convergence rates in multiagent learning

Speaker: Greg Hines

In this paper we study the use of experts algorithms in a multiagent setting.