Learning to Find a Goal

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Related lectures (32)

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Attractor Networks and Spiking Neurons

Explores attractor networks, spiking neurons, memory data, and realistic networks in neural dynamics.

Neural Architectures for Embodied AI and Cognition

Explores neural architectures for embodied AI, cognitive systems, and the integration of computing and robotics.

Neuroscience Inspired Artificial Intelligence

Explores the historical development of deep learning, reinforcement learning, attention mechanisms, and memory systems in AI inspired by neuroscience.

Spike-Timing Models of plasticity

Explores Spike-Timing Models of plasticity, including STDP and synaptic traces.

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Columnar Processing in the Cortex

Explores columnar processing in the cortex, decision-making tasks, and the transition from spatial information to action.

Modeling the role of hippocampus in spatial navigation

Discusses the role of the hippocampus in spatial navigation and the formation of place cell representation through recurrent network models.

Neuroscience and ML

Explores the intersection between neuroscience and machine learning, discussing deep learning, reinforcement learning, memory systems, and the future of bridging machine and human-level intelligence.

Eligibility Traces for Policy Gradient and Actor-Critic

Explores eligibility traces in policy gradient and actor-critic architectures, leading to an elegant online learning rule.

Scientific Computing in Neuroscience

Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.