This framework combines symbolic planning, counterfactual reasoning, reinforcement learning, and deep computer vision to detect and accommodate novelties. We introduce general algorithms for exploring open worlds using inference and machine learning methodologies to facilitate novelty accommodation.
This paper presents a novel cognitive architecture framework to handle open-world novelties combining symbolic planning, counterfactual reasoning, reinforcement ...
Jul 17, 2024 · This paper presents a novel cognitive architecture framework to handle open-world novelties. This framework combines symbolic planning, ...
Oct 13, 2024 · This paper presents a novel cognitive architecture framework to handle open-world novelties. This framework combines symbolic planning, ...
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A domain-independent agent architecture for adaptive operation in evolving open worlds.Shiwali Mohan, Wiktor Piotrowski, Roni Stern, Sachin Grover, Sookyung Kim ...
Jul 1, 2024 · These types of AI tools combine traditional knowledge-based models and data-driven deep neural network models to enable complex reasoning tasks ...
A neurosymbolic cognitive architecture framework for handling novelties in open worlds · Shivam Goel · Panagiotis Lymperopoulos · Ravenna Thielstrom · Evan Krause ...
Dive into the research topics of 'A Neurosymbolic Cognitive Architecture Framework for Handling Novelties in Open Worlds'. Together they form a unique ...
Jan 16, 2023 · We show that WorldCloner adapts to novelties more effi- ciently than state-of-the-art reinforcement learners. 2 BACKGROUND. Novelty-Handling.
We introduced NovelGym, a flexible platform tailored for the implementation and injection of novelties and easy task creation in gridworld environments. We ...