- Environment overview:
- Light dark domain with a discrete state space (grid world)
- If a move would end outside of the grid, the agent enters the grid again on the opposite side (e.g., agent leaves on the left side and enters on the right side)
- Initial belief: uniform over all possible states (except for goal state)
- Current set-up (A=agent, G=goal, L=light):
**AL*
*G*L*
***L*
***L*
- Behavior of the agent:
- No tendency to go in a particular direction in the first step
- Belief update: There seems to be something incorrect with either taking the probability density function to update the belief or with the probability density function itself (it gives probabilities > 1 which is not correct)
- Implemented a visualization tool for the tree:
Belief update: the belief update is actually correct. Even if the PDF gives high values, they are taken care of by the normalization factor of the Bayes update. In addition, I think that the bivariate Gaussian for the observation function in the light-dark domain can be simplified to the product of two univariate Gaussians because the variables involved in the observation are independent.
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