Automated Planning: Modeling and Constraints

Related lectures (31)

Page 3 of 4

Covers the basics and applications of predicate logic, including quantifiers, predicates, and propositional functions.

Explores the theory of constraints in molecular dynamics simulations, including the SHAKE algorithm.

Explores the rheology of materials, drawing parallels between cats' behavior and material properties.

Covers the method of Lagrange multipliers to find extrema subject to constraints.

Covers the basics of linear programming, defining corners, extreme points, and feasible solutions within polyhedrons.

Covers linear constraints in standard form, including equality constraints, rank, and redundant constraints.

Covers the KKT conditions for optimization with constraints, detailing their application and significance in solving constrained problems.

Covers optimization problems in path finding and portfolio allocation.

Covers sensitivity analysis in linear programming, focusing on optimal solutions and their sensitivities to changes.

Covers Euler's Elastica and the equilibrium shape of a bent beam using variational/energy methods.