Features

Solves discrete-time Markov Decision Problems using dynamic programming

Solves finite and infinite time problems

Uses either function or policy iteration for infinite horizon problems

Solves discounted and average return problems

Solves models with different stages

Solves problems with partial observability and model uncertainty (adaptive management)

Includes procedures for working with both explicit and implicit spatial models

State transitions can be expressed in terms of transition matrices or as functions

Interpolation over rectangular grids and simplex grids

Flexible input structure facilitates ease of use and efficient operation

Bayesian Influence Diagram approach to model specification is available

Includes tools for simulation, long-run analysis and graphic displays

60+ page User’s Guide

It’s free!