An ASP-based hybrid method enumerates geometrically admissible motion behaviors as stable models for environment-constrained trajectory computation in dynamic domains such as autonomous driving.
In: Proceedings of the 22nd International Conference on Principles of Knowledge Representation and Reasoning
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3representative citing papers
A framework mines spatial, functional, and qualitative commonsense constraints from SGG training data and uses them to correct ranked predictions at inference, yielding consistent gains on three benchmarks.
ASPEn integrates ASP stable-model semantics with energy-based models for joint discrete-continuous optimisation and end-to-end training on visual reasoning and multi-object tracking.
citing papers explorer
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Reasonable Motion: A General ASP Foundation for Environment Constrained Movement Trajectory Computation
An ASP-based hybrid method enumerates geometrically admissible motion behaviors as stable models for environment-constrained trajectory computation in dynamic domains such as autonomous driving.
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Visual Commonsense Driven Knowledge Refinements for Scene Graph Generation
A framework mines spatial, functional, and qualitative commonsense constraints from SGG training data and uses them to correct ranked predictions at inference, yielding consistent gains on three benchmarks.
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Answer Set Programming Energised! End-to-End Neurosymbolic Reasoning and Learning with ASP and Energy Based Models
ASPEn integrates ASP stable-model semantics with energy-based models for joint discrete-continuous optimisation and end-to-end training on visual reasoning and multi-object tracking.