mlsanityData to 7 Oct 2026

Cognitive Homeostatic Agents

arXiv 2103.03359 ↗First posted 27 Feb 2021cs.AI cs.LG cs.MAcited by 0

Not on the map. Why?

Abstract (arXiv)

Human brain has been used as an inspiration for building autonomous agents, but it is not obvious what level of computational description of the brain one should use. This has led to overly opinionated symbolic approaches and overly unstructured connectionist approaches. We propose that using homeostasis as the computational description provides a good compromise. Similar to how physiological homeostasis is the regulation of certain homeostatic variables, cognition can be interpreted as the regulation of certain 'cognitive homeostatic variables'. We present an outline of a Cognitive Homeostatic Agent, built as a hierarchy of physiological and cognitive homeostatic subsystems and describe structures and processes to guide future exploration. We expect this to be a fruitful line of investigation towards building sophisticated artificial agents that can act flexibly in complex environments, and produce behaviors indicating planning, thinking and feelings.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 55 references that are in the map. First posted on arXiv 27 Feb 2021.

Builds on

7 of 55 references.

References · 7

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2013Playing Atari with Deep Reinforcement Learningcited by 3,211
  3. 2019Solving Rubik's Cube with a Robot Handcited by 699
  4. 2019Challenges of Real-World Reinforcement Learningcited by 282
  5. 2019Meta-Learning Representations for Continual Learningcited by 189
  6. 2017The Consciousness Priorcited by 105
  7. 2017Neural Distributed Autoassociative Memories: A Surveycited by 12

Built on by

Not cited yet.