智能机器人的自适应自主Agents的建模

在问题求解期间及穿越动态的、不可预测的环境的过程中 ,真实世界的问题需要自适应的求解方法来‘裁剪’Agent的行为 ,并使其落入任务域 ,否则不完备的知识、不确定性、不确定的Agents及过程的存在、硬件失灵和不精确性都会引发不确定事件的发生。自适应自主Agents是一种存在于动态的、不可预测的环境中 ,并试图满足一系列随时间变化的目标或动机的系统 ,而且此类Agents在处理这些目标的过程中 ,能基于已有的经验改进其能力。自适应自主Agents为智能机器人实现这一目标提供了一种新的途径。主要讨论了智能机器人的自适应自主Agents的建模问题 ,并指出它的局限性和开问题

Modeling Adaptive Autonomous Agents for Intelligent Robots

Real world problems demand adaptive problem solver that can tailor their behavior to their task domain, both during a problem solving session and over time across a dynamic and unpredictable environment. Otherwise, incomplete knowledge, uncertainty, the presence of uncertainty agents and processes, and hardware failure and imprecision will conspire to cause uncertainty events, mission failure, and possibly damage to the agents. Autonomous agents are systems that inhabit a dynamic, unpredictable environment in which they try to satisfy a set of time dependent goals or motivations. Agents are said to be adaptive if they improve their competence at dealing with these goals based on experience. Research in autonomous agents has brought about a new way of excitement into the field of intelligent robots. This paper demonstrates modeling of adaptive autonomous agents for intelligent robots, and identifies its current limitations and open problems.