Jan van Eijck

About

Jan van Eijck is a distinguished researcher whose work bridges the foundational principles of logic with the practical challenges of artificial intelligence and robotics. His key research areas include dynamic logics, reinforcement learning, and autonomous systems, where he has made significant contributions to both theoretical frameworks and applied algorithms. Van Eijck’s seminal work, "The gamut of dynamic logics" (2006), provides a comprehensive exploration of logical systems for reasoning about change and action, earning 19 citations and solidifying his influence in computational logic. In robotics, his paper "On-line robot learning using the interval estimation algorithm" (2005) addresses a critical limitation in reinforcement learning: the impossibility of exploring a full state space during real-time RoboCup mid-size league games. By proposing a method to reduce the state space through selective behavior, van Eijck enabled more efficient on-line learning, a contribution that has informed subsequent algorithms in autonomous decision-making. His work exemplifies a rare ability to connect abstract logical theory with tangible robotic applications, making him a notable figure in the intersection of logic, learning, and robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   The gamut of dynamic logics

   19 citations · 2006
2. 2
   On-line robot learning using the interval estimation algorithm

   3 citations · 2005

Key Collaborators

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