Curiosity and Reward: Neuroscience to AI

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (29)

Variance and Covariance: Properties and Examples

Explores variance, covariance, and practical applications in statistics and probability.

Law of Large Numbers: Strong Convergence

Explores the strong convergence of random variables and the normal distribution approximation in probability and statistics.

Neural Architectures for Embodied AI and Cognition

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

Dynamic Programming: Optimal Decision Making

Explores dynamic programming for optimizing decision-making processes over time, using real-world examples like oil extraction and stock trading.

Estimators and Confidence Intervals

Explores bias, variance, unbiased estimators, and confidence intervals in statistical estimation.

The Marriage Problem

Explores the marriage problem, modeling the process as a controlled stochastic process with dynamic programming algorithms to find the optimal policy for accepting bachelors.

Dependence and Correlation

Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.

Factored Representations: Planning Efficiency

Explores factored representations for planning, focusing on reducing complexity and improving efficiency through separate feature modeling.

Combinatorial Principles: Factorials and Probabilities

Introduces combinatorial principles, factorials, probabilities, harmonic series convergence, and strategic decision-making in a romantic scenario.

Page 2 of 2