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Anticipatory Thinking Challenges in Open Worlds: Risk Management
StarCraft and Go are closed-world domains whose risks are known and mitigations well documented, ideal for learning through repetition.
Human in the Loop Novelty Generation
Developing artificial intelligence approaches to overcome novel, unexpected circumstances is a difficult, unsolved problem.
A Framework for Characterizing Novel Environment Transformations in General Environments
We introduce a formal and theoretical framework for defining and categorizing environment transformations, changes to the world an agent inhabits.
Self-directed Learning of Action Models using Exploratory Planning
Complex, real-world domains may not be fully modeled for an agent, especially if the agent has never operated in the domain before.
Computational Metacognition
Computational metacognition represents a cognitive systems perspective on high-order reasoning in integrated artificial systems that seeks to leverage ideas from human metacognition and from metareasoning approaches in artificial intelligence.
Anticipatory Thinking: A Metacognitive Capability
Anticipatory thinking is a complex cognitive process for assessing and managing risk in many contexts.
Dungeon Crawl Stone Soup as an Evaluation Domain for Artificial Intelligence
In this paper we provide (1) a description of the state space of Dungeon Crawl Stone Soup, (2) a description of the components for our API, and (3) the potential benefits of evaluating AI agents in the Dungeon Crawl Stone Soup video game.
