Abstract
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.
Original language | English |
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Title of host publication | Proceedings of the 8th International Conference on Agents and Artificial Intelligence (ICAART'16) |
Subtitle of host publication | February 24-26, 2016, in Rome, Italy |
Editors | Jaap van den Herik, Joaquim Felipe |
Publisher | SciTePress |
Pages | 322-329 |
Number of pages | 8 |
ISBN (Print) | 9789897581724 |
DOIs | |
Publication status | Published - 27 Apr 2016 |
Keywords
- Online planning
- BDI agent
- Risk awareness
- Decision making