what’s the latest?

more news please
  • a toolbox of principled learning paradigms

    RL team leader Haitham Bou-Ammar explains the diversity of learning paradigms used by PROWLER.io

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  • Social AI: a principled decision making paradigm, by Enrique Muñoz de Cote

    Multi-agent Systems team leader Enrique outlines how PROWLER.io is using game theory to help AI agents work together.

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  • Vishal on the couch at Unbound London

    PROWLER.io CEO Vishal Chatrath explains what…

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under the hood

The burgeoning AI industry is still focused on perception – recognising images, understanding speech, helping robots touch. But far greater benefits will come when AIs can make good, principled decisions based on those perceptions.
PROWLER.io’s Decision Making systems:
  • are autonomous
  • learn from experience
  • use Probabilistic models that are flexible enough to generalise to novel situations
  • adapt to changing environments by refining their strategies in data-driven ways
  • continually update their environmental models in light of data collected while operating.
  • use Reinforcement Learning (RL) algorithms that can help estimate, account for and even reduce uncertainty
  • can cope with the uncertainties of finite – even small – amounts of data
  • can favour decisions that loop back fresh information to models
  • use Game Theory to operate in multi-agent settings
  • can cooperate – and compete – by inferring what humans and other AIs are trying to do.

our core strategies

  • probabilistic modelling

  • reinforcement learning

  • multi-agent systems

how can our technology be used?

  • games

  • smart cities

  • robotic toys

  • autonomous vehicles

  • drones & robots