Tag Archives: Markov random fields

LM101-071: How to Model Common Sense Knowledge using First-Order Logic and Markov Logic Nets

Self-driving car doesn't see the difference between hitting a baby carriage or hitting a garbage can because it does not have common sense.

Podcast: Play in new window | Download | Embed

 LM101-071: How to Model Common Sense Knowledge using First-Order Logic and Markov Logic Nets Episode Summary: In this podcast, we provide some insights into the complexity of common sense. First, we discuss the importance of building common sense into learning machines. Second, we discuss how first-order logic can be used to represent common sense knowledge. Third, we describe… Read More »

LM101-039: How to Solve Large Complex Constraint Satisfaction Problems (Monte Carlo Markov Chain)[Rerun]

Robot trying to solve a probabilistic constraint satisfaction problem.

Podcast: Play in new window | Download | Embed

LM101-039: How to Solve Large Complex Constraint Satisfaction Problems (Monte Carlo Markov Chain) Episode Summary: In this episode we discuss how to solve constraint satisfaction inference problems where knowledge is represented as a large unordered collection of complicated probabilistic constraints among a collection of variables. The goal of the inference process is to infer the most probable values… Read More »