9,599 research outputs found
OWL-POLAR : A Framework for Semantic Policy Representation and Reasoning
Peer reviewedPreprin
GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling
We address the problem of efficient exploration for transition model learning
in the relational model-based reinforcement learning setting without extrinsic
goals or rewards. Inspired by human curiosity, we propose goal-literal babbling
(GLIB), a simple and general method for exploration in such problems. GLIB
samples relational conjunctive goals that can be understood as specific,
targeted effects that the agent would like to achieve in the world, and plans
to achieve these goals using the transition model being learned. We provide
theoretical guarantees showing that exploration with GLIB will converge almost
surely to the ground truth model. Experimentally, we find GLIB to strongly
outperform existing methods in both prediction and planning on a range of
tasks, encompassing standard PDDL and PPDDL planning benchmarks and a robotic
manipulation task implemented in the PyBullet physics simulator. Video:
https://youtu.be/F6lmrPT6TOY Code: https://git.io/JIsTBComment: AAAI 202
Neural systems supporting navigation
Highlights:
• Recent neuroimaging and electrophysiology studies have begun to shed light on the neural dynamics of navigation systems.
• Computational models have advanced theories of how entorhinal grid cells and hippocampal place cells might serve navigation.
• Hippocampus and entorhinal cortex provide complementary representations of routes and vectors for navigation.
Much is known about how neural systems determine current spatial position and orientation in the environment. By contrast little is understood about how the brain represents future goal locations or computes the distance and direction to such goals. Recent electrophysiology, computational modelling and neuroimaging research have shed new light on how the spatial relationship to a goal may be determined and represented during navigation. This research suggests that the hippocampus may code the path to the goal while the entorhinal cortex represents the vector to the goal. It also reveals that the engagement of the hippocampus and entorhinal cortex varies across the different operational stages of navigation, such as during travel, route planning, and decision-making at waypoints
Goal Directed Conflict Resolution and Policy Refinement
Peer reviewedPostprin
- …