Alternation open list

alternates between several open lists.

alt(sublists, boost=0)

• sublists (list of OpenList): open lists between which this one alternates

• boost (int): boost value for contained open lists that are restricted to preferred successors

Epsilon-greedy open list

Chooses an entry uniformly randomly with probability 'epsilon', otherwise it returns the minimum entry. The algorithm is based on

• Richard Valenzano, Nathan R. Sturtevant, Jonathan Schaeffer and Fan Xie.
  A Comparison of Knowledge-Based GBFS Enhancements and Knowledge-Free Exploration.
  In Proceedings of the Twenty-Fourth International Conference on Automated Planning and Scheduling (ICAPS 2014), pp. 375-379. AAAI Press, 2014.

epsilon_greedy(eval, pref_only=false, epsilon=0.2, random_seed=-1)

• eval (Evaluator): evaluator

• pref_only (bool): insert only nodes generated by preferred operators

• epsilon (double [0.0, 1.0]): probability for choosing the next entry randomly

• random_seed (int [-1, infinity]): Set to -1 (default) to use the global random number generator. Set to any other value to use a local random number generator with the given seed.

Pareto open list

Selects one of the Pareto-optimal (regarding the sub-evaluators) entries for removal.

pareto(evals, pref_only=false, state_uniform_selection=false, random_seed=-1)

• evals (list of Evaluator): evaluators

• pref_only (bool): insert only nodes generated by preferred operators

• state_uniform_selection (bool): When removing an entry, we select a non-dominated bucket and return its oldest entry. If this option is false, we select uniformly from the non-dominated buckets; if the option is true, we weight the buckets with the number of entries.

• random_seed (int [-1, infinity]): Set to -1 (default) to use the global random number generator. Set to any other value to use a local random number generator with the given seed.

Best-first open list

Open list that uses a single evaluator and FIFO tiebreaking.

single(eval, pref_only=false)

• eval (Evaluator): evaluator

• pref_only (bool): insert only nodes generated by preferred operators

Implementation Notes: Elements with the same evaluator value are stored in double-ended queues, called "buckets". The open list stores a map from evaluator values to buckets. Pushing and popping from a bucket runs in constant time. Therefore, inserting and removing an entry from the open list takes time O(log(n)), where n is the number of buckets.

Tie-breaking open list

tiebreaking(evals, pref_only=false, unsafe_pruning=true)

• evals (list of Evaluator): evaluators

• pref_only (bool): insert only nodes generated by preferred operators

• unsafe_pruning (bool): allow unsafe pruning when the main evaluator regards a state a dead end

Type-based open list

Uses multiple evaluators to assign entries to buckets. All entries in a bucket have the same evaluator values. When retrieving an entry, a bucket is chosen uniformly at random and one of the contained entries is selected uniformly randomly. The algorithm is based on

• Fan Xie, Martin Mueller, Robert Holte and Tatsuya Imai.
  Type-Based Exploration with Multiple Search Queues for Satisficing Planning.
  In Proceedings of the Twenty-Eigth AAAI Conference Conference on Artificial Intelligence (AAAI 2014), pp. 2395-2401. AAAI Press, 2014.

type_based(evaluators, random_seed=-1)

• evaluators (list of Evaluator): Evaluators used to determine the bucket for each entry.

• random_seed (int [-1, infinity]): Set to -1 (default) to use the global random number generator. Set to any other value to use a local random number generator with the given seed.