How to understand biological intelligence?
Defining intelligence is quite intricate and controversial. All the biological agents look intelligent in some ways compared with non-biological physical phenomena. Complexity cannot be the primary determinant, as the physical world is already complex enough. While not being sufficient, the necessary feature of intelligence that has been distilled from agelong debates is the ability to adapt to different environments and situations. Since the adaptability is an inevitable consequence of evolution, some flavour of intelligence is scented with all biological processes, not to mention agents. By framing the problem in this way, understanding biological intelligence may be reduced to the question how biological systems adjust, modify, and improve themselves by using past interactions with the environment. Learning theory especially reinforcement learning is an essential tool to address the question. In this 3days exploration, we study how reinforcement learning works, survey a variety of intelligent biological behaviours, and discuss how such behaviours can be understood with the aid of reinforcement learning and other learning theory.
Day1 & Day2: Lecture on reinforcement learning
The first two days are dedicated to providing basic knowledge and information on what is reinforcement learning and how it works in principle. The lecturer, Antonio Celani, is a specialist in reinforcement learning with a physics background and biological motivations. His lecture would be the best introductory one to physicists and biologists, not to mention others.
Day3: Workshop for RL & Biological Intelligence
The last day focuses on various types of intelligent biological phenomena and on how reinforcement learning can be employed to understand the underlying principles of those phenomena. The speakers will touch on a variety of phenomena from sensing and searching behaviours of different cells and organisms to immunity as well as the cutting-edge research on learning theory.
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