pomdp_1.1.1

pomdp 1.1.1 09/04/2023)

Changes

• plot_policy_graph(): The parameter order has slightly changed; belief_col is now called state_col;
  unreachable states are now suppressed.
• policy() gained parameters alpha and action.
• color palettes are now exported.
• POMPD accessors gain parameter drop.
• POMDP constructor and read_POMDP gained parameter normalize and, by default, normalize
  the POMDP definition.

New Features

• Large POMDP descriptions are now handled better by keeping the reward as a data.frame and
  supporting sparse matrices in the C++ code.
• New function value_function() to access alpha vectors.
• New function regret() to calculate the regret of a policy.
• transition_graph() to visualize the transition model.
• Problem descriptions are now normalized by default.

pomdp 1.1.0 (01/23/2023)

New Features

• Added C++ (Rcpp) support. Speed up for simulate_POMDP, sample_belief_space, reward, ...
• simulate_POMDP and sample_belief_space now have parallel (foreach) support.
• Sparse matrices from package Matrix for matrices with a density below 50%.
• Added support to parse matrices for POMDP files.
• Added model normalization.
• is_solved_POMDP(), is_converged_POMDP(), is_timedependent_POMDP(), and is_solved_MDP() are now exported.

Changes

• accessors are now called now transition_val() and observation_val().
• simulate_POMDP() and simulate_MDP() now return a list.
• reimplemented round_stochastic() to improve speed.
• MDP policy now uses factors for actions.
• estimate_belief_for_nodes() now can also use trajectories to estimate beliefs faster.
• cleaned up the interface for episodes and epochs.