Date: 11 Feb 2003

UBU Team

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The aim of developing UBU is to subject a series of tools and procedures for agent decision support to a dynamic real-time domain. These tools and procedures have previously been tested in various other domains, e.g., intelligent buildings [2] and social simulations [6]. The harsh time constraints of RoboCup requires true bounded rationality, however, as well as the development of anytime algorithms not called for in less constrained domains (cf. [3]). Artificial decision makers are in the AI and agent communities usually associated with planning and rational (as in utility maximising) behaviour. We have instead argued for the coupling of the reactive layer directly to decision support. A main hypothesis is that in dynamic domains (such as RoboCup), time for updating plans is insufficient. Basically depending on the size requirements of agents, and on the communication facilities available to the agents, we have placed decision support either in the agents, or externally. In the former case, deliberation is made in a decision module. In the latter case, a kind of external calculator which we have named pronouncer provides rational action alternatives. The input to the pronouncer is decision trees or influence diagrams. The structure and size of these models are kept small, to guarantee fast evaluation (cf. [7]). The pronouncer can be made into an agent too, e.g., by using a wrapper. The coach function is particularly interesting in this context, since it is “free” and since it could hold the pronouncer code. An important problem here is the uncertainty and space constraints on the communication with the coach. The concept of norms as constraints on agent actions has also been investigated [1]. A team in which each boundedly rational player maximises its individual expected utility does not yield the best possible team: Group constraints on actions must be taken into account (see, e.g., [4]). Norms is our way of letting the coalitions that an agent is part of play a part in the deliberation of the agent.