Getting Robots, Agents and People to Cooperate: An Initial Report
نویسندگان
چکیده
Combining the unique capabilities of robots, agents and people (RAPs) promises to improve the safety, efficiency, reliability and cost at which some goals can be achieved, while allowing the achievement of other goals not previously achievable. Despite their heterogeneity, and indeed, because of their heterogeneity, our key hypothesis is that in order for RAPs to work together effectively, they must work as a team: they should be aware of the overall goals of the team, and coordinate their activities with their fellow team members in order to further the team’s goals. This poses a challenge, since different RAP entities may have differing social abilities and hence differing abilities to coordinate with their teammates. To construct such RAP teams, we make the RAPs “team ready” by providing each of them with teamwork-enabled proxies. While proxy-based architectures have been explored earlier for flexible multiagent teamwork, their application to RAP teams exposes two weaknesses. To address the problems with existing role allocation algorithms for RAP teams operating in dynamic environments, we provide a new approach for highly flexible role allocation and reallocation. Second, we enrich the communication between RAPs and between a RAP and its proxy, to improve teamwork flexibility while limiting the number of messages exchanged. This paper discusses the proxy based architecture and our initial attempts at developing algorithms that address the problems that emerge when the RAP teams are used in complex do-
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My research focuses on investigating how robots and other agents should learn and cooperate in order to tackle realworld problems. Agents are entities that repeatedly interact with their environment in order to accomplish their goals. In order for robots and other agents to handle many real-world problems, they must be able to cooperate with other agents and humans. However, they may not always...
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