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Tokyo Institute of Technology

Earth-Life Science Institute

Robust and emergent Physarum logical-computing
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    •   11  
      Engineering, Computational Logic, Computational Biology, Bio-Inspired Systems
Amoeba-based neurocomputing with chaotic dynamics
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    •   12  
      Complex Systems Science, Dynamical Systems, Decision Making, Combinatorial Optimization
Beyond input-output computings: Error-driven emergence with parallel non-distributed slime mold computer
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    •   27  
      Engineering, Distributed Computing, Artificial Intelligence, Cybernetics
Spontaneous deadlock breaking on amoeba-based neurocomputer
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    •   17  
      Engineering, Resource Allocation, Bio-Inspired Systems, Information Processing
Resolution of infinite-loop in hyperincursive and nonlocal cellular automata: Introduction to slime mold computing
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    • Spacetime Studies
Amoeba-based chaotic neurocomputing: Combinatorial optimization by coupled biological oscillators
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    •   13  
      Artificial Intelligence, Complex Systems Science, Dynamical Systems, Decision Making
Amoeba-based emergent computing: combinatorial optimization and autonomous meta-problem solving
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    • Unconventional Computing
Material implementation of hyperincursive field on slime mold computer
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    •   7  
      Complex Systems, Science and Technology, Distributed System, Complex System
Resource-competing oscillator network as a model of amoeba-based neurocomputer
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    •   12  
      Complex Systems Science, Dynamical Systems, Decision Making, Combinatorial Optimization
Tug-of-war model for the two-bandit problem: Nonlocally-correlated parallel exploration via resource conservation
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    •   10  
      Complex Systems Science, Dynamical Systems, Decision Making, Decision And Game Theory
Spontaneous mode switching in coupled oscillators competing for constant amounts of resources
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    •   10  
      Complex Systems Science, Dynamical Systems, Decision Making, Decision And Game Theory
Simulation of Neurocomputing Based on Photophobic Reactions of Euglena: Toward Microbe–Based Neural Network Computing
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    •   20  
      Engineering, Monte Carlo Simulation, Bio-Inspired Systems, Neural Network
Tug-of-war model for multi-armed bandit problem
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    •   7  
      Decision Making, Reinforcement Learning, Unconventional Computation, Unconventional Computing
Amoeba-Based Knowledge Discovery
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    •   8  
      Data Mining, Neural Network, Genetic Algorithm, Traditional Knowledge
Greedy versus social: resource-competing oscillator network as a model of amoeba-based neurocomputer
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    •   12  
      Complex Systems Science, Dynamical Systems, Decision Making, Combinatorial Optimization
Local Semantics for the Part-whole Problem: An Alternative CA Model Based on Unserializable Parallel Processing
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    •   4  
      Cellular Automata, Parallel Processing, Science and Technology, Complex System
Simulation of neurocomputing based on the photophobic reactions of Euglena with optical feedback stimulation
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    •   20  
      Engineering, Monte Carlo Simulation, Bio-Inspired Systems, Neural Network
Amoeba-Based Knowledge Discovery System
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    •   8  
      Data Mining, Neural Network, Genetic Algorithm, Traditional Knowledge
Autonomous selection and indefinite goals: A system using Bezier curves as dynamically re-defined transition rules
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    •   5  
      Dynamical Systems, Splines approximation, Chaos, Rule Dynamics
Adaptive Tug-of-war Model for Two-armed Bandit Problem
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