Collaborative Multiagent Framework Based on Online Risk Aware Planning and Decision Making. In Proceedings of the 28th International Conference on Tools with Artificial Intelligence (pp. 25 32) (Proceedings of the International Conference on Tools with Artificial Intelligence (ICTAI)
The ability of an autonomous agent to select rational actions is vital in enabling it to achieve its goals. To do so effectively in a high stakes setting, the agent must be capable of considering the risk and potential reward of both immediate and future actions. In this paper we provide a novel method for calculating risk alongside utility in online planning algorithms. We integrate such a risk aware planner with a BDI agent, allowing us to build agents that can set their risk aversion levels dynamically based on their changing beliefs about the environment. To guide the design of a risk aware agent we propose a number of principles which such an agent should adhere to and show how our proposed framework satisfies these principles. Finally, we evaluate our approach and demonstrate that a dynamically risk averse agent is capable of achieving a higher success rate than an agent that ignores risk, while obtaining a higher utility than an agent with a static risk attitude.