Belief-based Stability in Coalition Formation with by Dr. Chi-kong Chan, Prof. Ho-fung Leung (auth.)

By Dr. Chi-kong Chan, Prof. Ho-fung Leung (auth.)

Belief-based balance in Coalition Formation with UncertaintyAn clever brokers’ Perspective discusses coalition balance. It extends the vintage balance idea of the non-transferable application center via offering new belief-based balance standards lower than uncertainty, and illustrates how the hot notion can be utilized to research the steadiness of a brand new form of belief-based coalition formation video game.

The e-book is meant for graduate scholars, engineers, and researchers within the box of synthetic intelligence and machine science.

Chi-kong Chan is a laboratory supervisor and a vacationing lecturer on the Hong Kong Polytechnic college, China; Ho-fung Leung is a Professor and the Chairman of division of desktop technological know-how and Engineering, The chinese language collage of Hong Kong, China.

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Additional resources for Belief-based Stability in Coalition Formation with Uncertainty: An Intelligent Agents’ Perspective

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6 while the worth of all other coalitions remain unchanged, then the core will become empty. In other words, for any feasible allocation (xF , xG , xH ), there must be a subset of agents that is motivated to break away. 6), or these companies will form a smaller coalition for the profit of $1 million. 7. 5 millions of profit. There are also other stability criteria proposed for TU games, for instances, the stable set [5] and the kernel [8], which we will not discuss because they are out of the scope of this book.

For example, a tennis coalition of four agents is 36 Chapter 3 Two Classes of Stability — Strong Core and Weak Core always more preferable than two tennis coalitions of two tennis players each. We also assume that all agents in the same coalition perform the same activity (playing tennis or watching movie). That is, we do not allow some agents in a group to watch movie while some others play tennis, or vice versa, otherwise they cannot be said to be in a group. Finally, for ease of analysis, we assume that if any agents decide to play tennis, they do not need to go in groups of even number of players, with an understand that this is always possible if we assume that an agent can always go to play tennis in a tennis club where a partner is not difficulty to find.

As mentioned above, the existing probability-based solution concepts are unsuitable for this type of games for two reasons. First, these existing works focus mainly on games with transferable utilities. Second, there are cases where a probabilistic model is not suitable, such as multi-agent cooperation games where the samples (agents’ experiences) are too sparse to provide any meaningful estimation of the probability distributions, as seen in the scenario considered in this section. I. systems.

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