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mon approaches, but certain themes did recur in this work Recurring themes were the rejection of architectures based on symbolic representations, an emphasis on a closer coupling between the agent's environment and the action it performs, and the idea that intelligent behaviour can be seen to emerge from the interaction of a number of much simpler behaviours The term 'furore' might reasonably be used to describe the response from the symbolic and logical reasoning communities to the emergence of behavioural AI Some researchers seemed to feel that behavioural AI was a direct challenge to the beliefs and assumptions that had shaped their entire academic careers Not surprisingly, they were not predisposed simply to abandon their ideas and research programs I do not believe there was (or is) a clear cut 'right' or 'wrong' in this debate.

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With the benefit of hindsight, it seems clear that much symbolic A1 research had wandered into the realms of abstract theory, and did not connect in any realistic way with the reality of building and deploymg agents in realistic scenarios It also seems clear that the decomposition of A1 into components such as planning and learning, without any emphasis on synthesizing these components into an integrated architecture, was perhaps not the best strategy for A1 as a discipline But it also seems that some claims made by members of the behavioural community were extreme, and in many cases suffered from the over-optimism that A1 itself suffered from in its early days The practical implications of all this were threefold The first was that the behavioural A community to a certain extent split 1 off from the mainstream AI community.

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Taking inspiration from biological metaphors, many of the researchers in behavioural AI began working in a community that is today known as 'artificial life' (alife) The second was that mainstream A1 began to recognize the importance of integrating the components of intelligent behaviour into agents, and, from the mid-1980s to the present day, the area of agent archtectures has grown steadily in importance The third was that within AI, the value of testing and deploymg agents in realistic scenarios (as opposed to simple, contrived, obviously unrealistic scenarios) was recognized This led to the emergence of such scenarios as the RoboCup robotic soccer challenge, in which the aim is to build agents that can actually play a game of soccer against a team of robotic opponents (RoboCup, 2001) So, by the mid-1980s, the area of agent architectures was becoming established as a specific research area within AI itself.

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Most researchers in the agent community accept that neither a purely logicist or reasoning approach nor a purely behavioural approach is the best route to building agents capable of intelligent autonomous action Intelligent autonomous.

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