[图书][B] A concise introduction to models and methods for automated planning
Planning is the model-based approach to autonomous behavior where the agent behavior is
derived automatically from a model of the actions, sensors, and goals. The main challenges …
derived automatically from a model of the actions, sensors, and goals. The main challenges …
PROST: Probabilistic planning based on UCT
T Keller, P Eyerich - Proceedings of the International Conference on …, 2012 - ojs.aaai.org
We present PROST, a probabilistic planning system that is based on the UCT algorithm by
Kocsis and Szepesvari (2006), which has been applied successfully to many areas of …
Kocsis and Szepesvari (2006), which has been applied successfully to many areas of …
Simulated penetration testing: From" dijkstra" to" turing test++"
J Hoffmann - Proceedings of the international conference on …, 2015 - ojs.aaai.org
Penetration testing (pentesting) is a well established method for identifying security
weaknesses, by conducting friendly attacks. Simulated pentesting automates this process …
weaknesses, by conducting friendly attacks. Simulated pentesting automates this process …
Trial-based heuristic tree search for finite horizon MDPs
Dynamic programming is a well-known approach for solving MDPs. In large state spaces,
asynchronous versions like Real-Time Dynamic Programming have been applied …
asynchronous versions like Real-Time Dynamic Programming have been applied …
MCTS based on simple regret
D Tolpin, S Shimony - Proceedings of the AAAI Conference on Artificial …, 2012 - ojs.aaai.org
UCT, a state-of-the art algorithm for Monte Carlo tree search (MCTS) in games and Markov
decision processes, is based on UCB, a sampling policy for the Multi-armed Bandit problem …
decision processes, is based on UCB, a sampling policy for the Multi-armed Bandit problem …
A comparison of Monte Carlo tree search and rolling horizon optimization for large-scale dynamic resource allocation problems
Dynamic resource allocation (DRA) problems constitute an important class of dynamic
stochastic optimization problems that arise in many real-world applications. DRA problems …
stochastic optimization problems that arise in many real-world applications. DRA problems …
Multi-modal journey planning in the presence of uncertainty
A Botea, E Nikolova, M Berlingerio - Proceedings of the International …, 2013 - ojs.aaai.org
Multi-modal journey planning, which allows multiple types of transport within a single trip, is
becoming increasingly popular, due to a strong practical interest and an increasing …
becoming increasingly popular, due to a strong practical interest and an increasing …
Simple regret optimization in online planning for Markov decision processes
Z Feldman, C Domshlak - Journal of Artificial Intelligence Research, 2014 - jair.org
We consider online planning in Markov decision processes (MDPs). In online planning, the
agent focuses on its current state only, deliberates about the set of possible policies from …
agent focuses on its current state only, deliberates about the set of possible policies from …
Monte Carlo tree search with heuristic evaluations using implicit minimax backups
Monte Carlo Tree Search (MCTS) has improved the performance of game engines in
domains such as Go, Hex, and general game playing. MCTS has been shown to outperform …
domains such as Go, Hex, and general game playing. MCTS has been shown to outperform …
Long-term robot navigation in indoor environments estimating patterns in traversability changes
L Nardi, C Stachniss - 2020 IEEE International Conference on …, 2020 - ieeexplore.ieee.org
Nowadays, mobile robots are deployed in many indoor environments such as offices or
hospitals. These environments are subject to changes in the traversability that often happen …
hospitals. These environments are subject to changes in the traversability that often happen …