Towards a Generic Infrastructure to Adjust the Autonomy of Soar Agents.
Scott A. Wallace, Matthew H. Henry · 2008
Developing and testing intelligent agents is a complex task that is both time-consuming and costly. This creates the potential that problems in the agent’s behavior will be re-alized only after the agent has been put to use. In this pa-per we explore two implementations of a generic agent self-assessment framework applied to the Soar agent architecture. Our system extends previous work and can be used to achieve adjustable levels of agent autonomy or runtime verification with only minor modifications to existing Soar agents. We present results indicating the computational overhead of both approaches compared against an agent that exhibits identical behavior without the help of the self-assessment framework. Agents whose behavior has not been completely validated run the risk of performing their tasks incorrectly. Such sit-