Tal Kachman

Research

My main research focus is on multiagent interaction, complex systems and reinforcement learning, with applications spanning from theoretical foundations to practical implementations.

Current Research Areas

Machine Learning & AI

  • Classical and deep Reinforcement learning
  • Multiagent systems
  • Diffusion based generative models
  • Algorithmic foundations of machine and deep learning

Complex Systems & Game Theory

  • Computational game theory
  • Complex systems analysis
  • Lyapunov exponents for diversity
  • Bifurcations in differentiable games

Quantum Computing

  • Quantum machine learning
  • Quantum space distance estimation
  • Quantum walk algorithms
  • Quantum topological classification

Previous Research (Physics Background)

  • Non-equilibrium statistical mechanics
  • Foundations of quantum mechanics
  • Quantum chaos
  • Molecular dynamics and computational chemistry
  • Nonlinear optics
  • Heat conduction in nanometric systems