We present a framework that incorporates the principle of bounded rationality into dynamic stochastic pursuit-evasion games. The solution of a stochastic game is
generally characterized by its (Nash) equilibria in feedback form, whose calculation may require extensive computational resources. In this paper, the agents are modeled as bounded rational entities with limited computational capabilities. We illustrate the proposed framework by applying it to a pursuit-evasion game between two aerial vehicles in a stochastic wind field. We show how such a game may be discretized and
properly analyzed by casting it as an iterative sequence of finite-state Markov Decision Processes (MDPs). Leveraging tools and algorithms from the cognitive hierarchy theory (“level-k thinking”) we compute the solution of the ensuing discrete game, while taking into consideration the rationality level of each agent. We also present an online algorithm for
each agent to infer its opponent's rationality level.
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The Design of Co-Robotic Games for Computer Science Education
Digital games featuring programmable agents are popular tools for teaching coding and computational thinking skills. However, today's games perpetuate an arguably obsolete relationship between programmable agents and human operators. Borrowing from the field of human-robotics interaction, we argue that collaborative robots, or cobots, are a better model for thinking about computational agents, working directly with humans rather than in place of or at arm's length from them. In this paper, we describe an initial design inquiry into the design of “cobot games”, programmable agent scenarios in which players program an in-game ally to assist them in accomplishing gameplay objectives. We detail three questions that emerged out of this exploration, our present thinking on them, and plans for deepening inquiry into cobot game design moving forward.
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- Award ID(s):
- 1906753
- NSF-PAR ID:
- 10340224
- Date Published:
- Journal Name:
- CHI PLAY '21: Extended Abstracts of the 2021 Annual Symposium on Computer-Human Interaction in Play
- Page Range / eLocation ID:
- 111 to 116
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3450337.3483472
