Difference between revisions of "Simulacia POMDP"
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== Results == | == Results == | ||
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Results of simulation with horizon=10 | Results of simulation with horizon=10 | ||
[[Image:pomdp_graph.png | 1100px]] | [[Image:pomdp_graph.png | 1100px]] | ||
Revision as of 00:56, 5 July 2016
Project objective
The goal of this project was to create a program for computation and evaluation of POMDP algorithm on simple two-state scenario. More precisely, my script computes piecewise linear value function over belief space for a given time horizon, then this result is used in a simulation of an agent with incomplete state awareness.
Requirements
This project can be run with either Python 2.7 or higher. Python 3.x is also supported. Another requirement is installed Matplotlib module for value function plotting.
Parameters of the example
The simulated scenario consists of an robot agent with two possible states and three actions, two of which are terminal actions (can be taken only once). Each terminal action has some associated reward, depending on the state of the agent.
The actions u1 and u2 are terminal actions.
The action u3 is a sensing action that potentially leads to a state transition.
The horizon is finite and γ=1.
Results
Results of simulation with horizon=10
