2013/03/28 by Chrisantha Fernando, Fernando, Chrisantha, Vera Vasas +1
Computer Science · Social Sciences · #Artificial Intelligence (cs.AI) #Computability, Logic, AI Algorithms #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Language and cultural evolution #cs.AI
paper · pdf · doi:10.48550/arxiv.1303.7201
Submitted as Part 2 to Living Machines 2013, Natural History Museum, London. Code available on github as it is being developed to implement the cognitive architecture above, here... https://github.com/ctf20/DarwinianNeurodynamics
arxiv created 2013/03/28 · openalex publication_date 2013/03/28 · arxiv updated 2013/03/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The accumulation of adaptations in an open-ended manner during lifetime learning is a holy grail in reinforcement learning, intrinsic motivation, artificial curiosity, and developmental robotics. We present a specification for a cognitive architecture that is capable of specifying an unlimited range of behaviors. We then give examples of how it can stochastically explore an interesting space of adjacent possible behaviors. There are two main novelties; the first is a proper definition of the fitness of self-generated games such that interesting games are expected to evolve. The second is a modular and evolvable behavior language that has systematicity, productivity, and compositionality, i.e. it is a physical symbol system. A part of the architecture has already been implemented on a humanoid robot.