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Nicholas R. Jennings
Researcher at Imperial College London
Publications - 823
Citations - 65994
Nicholas R. Jennings is an academic researcher from Imperial College London. The author has contributed to research in topics: Multi-agent system & Autonomous agent. The author has an hindex of 116, co-authored 807 publications receiving 64112 citations. Previous affiliations of Nicholas R. Jennings include University of Warsaw & University of Southampton.
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Cooperative Information Sharing to Improve Distributed Learning in Multi-Agent Systems
TL;DR: In this article, the authors propose a post-task completion sharing protocol for the distribution of state information between agents in a partially-observable domain, where the accuracy and timeliness of the communicated information determine the fidelity of the learned estimates and the usefulness of the actions taken based on these.
Valuing Search and Communication in Partially-Observable Coordination Problems (Extended Abstract)
TL;DR: In this paper, the authors extend the class of Bayesian coordination games to include explicit observation and communication, and argue that this class of games is appropriate for situations where the agents observation, communication and payoff earning actions are limited by some common resource, without introducing arbitrary penalties for communicating.
Reasoning about commitments in multiple concurrent negotiations
TL;DR: In this article, the authors consider the situation in which a buyer agent is looking for a single service provider from a number of available ones in its environment and provide and evaluate a commitment manager and integrate it into the negotiation model.
Poster abstract. Applying extended kalman filters to adaptivethermal modelling in homes
TL;DR: In this paper, an extended Kalman filter is used for parameter estimation for a room in a family home to obtain sufficient knowledge of the thermal dynamics of the home to build an adaptive thermal model.
Flexibly Priced Options: A New Mechanism for Sequential Auctions with Complementary Goods.
TL;DR: This work proposes a novel option pricing mechanism for reducing the exposure problem encountered by bidders with complementary valuations when participating in sequential, second-price auction markets, and shows that it can achieve better market allocation efficien y, at an only marginal cost to seller revenues.