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Found 7 papers, 1 papers with code
A Unifying Bayesian Formulation of Measures of Interpretability in Human-AI
Existing approaches for generating human-aware agent behaviors have considered different measures of interpretability in isolation.
Contrastive Explanations of Plans Through Model Restrictions
We formally define model-based compilations in PDDL2. 1 of each constraint derived from a user question in the taxonomy, and empirically evaluate the compilations in terms of computational complexity.
A Bayesian Account of Measures of Interpretability in Human-AI Interaction
Existing approaches for the design of interpretable agent behavior consider different measures of interpretability in isolation.
FAPE: a Constraint-based Planner for Generative and Hierarchical Temporal Planning
FAPE's representation coherently integrates flexible timelines with hierarchical refinement methods that can provide efficient control knowledge.
Explicability? Legibility? Predictability? Transparency? Privacy? Security? The Emerging Landscape of Interpretable Agent Behavior
There has been significant interest of late in generating behavior of agents that is interpretable to the human (observer) in the loop.
Extracting Lifted Mutual Exclusion Invariants from Temporal Planning Domains
We show that, in turn, this reduction in the number of variables reflects positively on the performance of a number of temporal planners that use a variable/value representation by significantly reducing their running time.
The Metrics Matter! On the Incompatibility of Different Flavors of Replanning
An open question is whether these metrics are interchangeable; answering this requires a normalized comparison of the various replanning quality metrics.
