Humanoid robots dynamically navigate an environment by interacting with it via contact
wrenches exerted at intermittent contact poses. Therefore, it is important to consider …

Beam search is a popular satisficing approach to heuristic search problems that allows one
to trade increased computation time for lower solution cost by increasing the beam width …

LAMA-2011 (Richter and Westphal 2010) is the clear winner of the sequential satisficing
track in the latest International Planning Competition (IPC-2011). It finds a first solution by …

The development of domain-independent planners within the AI Planning community is
leading to “off the shelf” technology that can be used in a wide range of applications …

The introduction of the concept of state novelty has advanced the state of the art in
deterministic online planning in Atari-like problems and in planning with rewards in general …

Recently, a number of papers have shown that for many domains, using multiple heuristics
in independent searches performs better than combining them into a single heuristic …

Utilizing multiple queues in Greedy Best-First Search (GBFS) has been proven to be a very
effective approach to satisficing planning. Successful techniques include extra queues …

Abstract Greedy Best-First Search (GBFS) is a powerful algorithm at the heart of many state
of the art satisficing planners. One major weakness of GBFS is its behavior in so-called …

A classical result in optimal search shows that A* with an admissible and consistent heuristic
expands every state whose f-value is below the optimal solution cost and no state whose f …

Best-first search algorithms such as A* need to apply tie-breaking strategies in order to
decide which node to expand when multiple search nodes have the same evaluation score …