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Planning as theorem proving in situation calculus was abandoned 50 years ago as an impossible project. But we have developed a Theorem Proving Lifted Heuristic (TPLH) planner that searches for a plan in a tree of situations using the A*…

Artificial Intelligence · Computer Science 2023-06-21 Mikhail Soutchanski , Ryan Young

Scheduling languages express to a compiler a sequence of optimizations to apply. Compilers that support a scheduling language interface allow exploration of compiler optimizations, i.e., exploratory compilers. While scheduling languages…

Programming Languages · Computer Science 2024-10-29 Mary Hall , Cosmin Oancea , Anne C. Elster , Ari Rasch , Sameeran Joshi , Amir Mohammad Tavakkoli , Richard Schulze

SAPA is a domain-independent heuristic forward chaining planner that can handle durative actions, metric resource constraints, and deadline goals. It is designed to be capable of handling the multi-objective nature of metric temporal…

Artificial Intelligence · Computer Science 2011-06-28 M. Do , S. Kambhampati

In this paper, we develop a Topological Approximate Dynamic Programming (TADP) method for planningin stochastic systems modeled as Markov Decision Processesto maximize the probability of satisfying high-level systemspecifications expressed…

Optimization and Control · Mathematics 2020-08-04 Lening Li , Jie Fu

Using LLMs not to predict plans but to formalize an environment into the Planning Domain Definition Language (PDDL) has been shown to improve performance and control. While most existing methodology only applies to fully observable…

Artificial Intelligence · Computer Science 2026-04-10 Liancheng Gong , Wang Zhu , Jesse Thomason , Li Zhang

This paper introduces time window temporal logic (TWTL), a rich expressivity language for describing various time bounded specifications. In particular, the syntax and semantics of TWTL enable the compact representation of serial tasks,…

Formal Languages and Automata Theory · Computer Science 2016-02-16 Cristian-Ioan Vasile , Derya Aksaray , Calin Belta

Recent large language models (LLMs) are promising for making decisions in grounded environments. However, LLMs frequently fail in complex decision-making tasks due to the misalignment between the pre-trained knowledge in LLMs and the actual…

Computation and Language · Computer Science 2023-10-27 Siqi Ouyang , Lei Li

Table reasoning tasks have shown remarkable progress with the development of large language models (LLMs), which involve interpreting and drawing conclusions from tabular data based on natural language (NL) questions. Existing solutions…

Computation and Language · Computer Science 2024-10-11 Yuan Sui , Jiaru Zou , Mengyu Zhou , Xinyi He , Lun Du , Shi Han , Dongmei Zhang

Large language models (LLMs) have recently demonstrated the potential in acting as autonomous agents for sequential decision-making tasks. However, most existing methods either take actions greedily without planning or rely on static plans…

Computation and Language · Computer Science 2023-06-01 Haotian Sun , Yuchen Zhuang , Lingkai Kong , Bo Dai , Chao Zhang

In recent years, imitation-based driving planners have reported considerable success. However, due to the absence of a standardized benchmark, the effectiveness of various designs remains unclear. The newly released nuPlan addresses this…

Robotics · Computer Science 2023-09-20 Jie Cheng , Yingbing Chen , Xiaodong Mei , Bowen Yang , Bo Li , Ming Liu

I comment on the PDDL 2.1 language and its use in the planning competition, focusing on the choices made for accommodating time and concurrency. I also discuss some methodological issues that have to do with the move toward more expressive…

Artificial Intelligence · Computer Science 2011-10-13 H. A. Geffner

Current Information Seeking (InfoSeeking) agents struggle to maintain focus and coherence during long-horizon exploration, as tracking search states, including planning procedure and massive search results, within one plain-text context is…

Computation and Language · Computer Science 2026-02-09 Tian Lan , Felix Henry , Bin Zhu , Qianghuai Jia , Junyang Ren , Qihang Pu , Haijun Li , Longyue Wang , Zhao Xu , Weihua Luo

Recognition of goals and plans using incomplete evidence from action execution can be done efficiently by using planning techniques. In many applications it is important to recognize goals and plans not only accurately, but also quickly. In…

Artificial Intelligence · Computer Science 2017-02-08 Ramon Fraga Pereira , Felipe Meneguzzi

Multi-step LLM reasoning over structured tables fails because planning and execution share no explicit cell-grounding contract. Existing methods constrain the planner to a left-to-right factorization at odds with table permutation…

Artificial Intelligence · Computer Science 2026-05-15 Tung Sum Thomas Kwok , Zeyong Zhang , Xinyu Wang , Chunhe Wang , Xiaofeng Lin , Hanwei Wu , Lei Ding , Guang Cheng , Zhijiang Guo

Temporal logic is a framework for representing and reasoning about propositions that evolve over time. It is commonly used for specifying requirements in various domains, including hardware and software systems, as well as robotics.…

Computation and Language · Computer Science 2024-06-03 İlker Işık , Ebru Aydin Gol , Ramazan Gokberk Cinbis

Task planning with temporally extended goals (TEGs) is a critical challenge in AI and robotics, enabling agents to achieve complex sequences of objectives over time rather than addressing isolated, immediate tasks. Linear Temporal Logic on…

Artificial Intelligence · Computer Science 2026-01-21 Yuliia Suprun , Khen Elimelech , Lydia E. Kavraki , Moshe Y. Vardi

Legal reasoning requires not only correct outcomes but also procedurally compliant reasoning processes. However, existing methods lack mechanisms to verify intermediate reasoning steps, allowing errors such as inapplicable statute citations…

Artificial Intelligence · Computer Science 2026-02-13 Xinyu Yang , Chenlong Deng , Tongyu Wen , Binyu Xie , Zhicheng Dou

Maintaining a map online is resource-consuming while a robust navigation system usually needs environment abstraction via a well-fused map. In this paper, we propose a mapless planner which directly conducts such abstraction on the unfused…

Robotics · Computer Science 2020-11-12 Jialin Ji , Zhepei Wang , Yingjian Wang , Chao Xu , Fei Gao

Autonomous exploration in complex and cluttered environments is essential for various applications. However, there are many challenges due to the lack of global heuristic information. Existing exploration methods suffer from the repeated…

Robotics · Computer Science 2024-11-22 Bo Zhou , Chuanzhao Lu , Yan Pan , Fu Chen

Many known planning tasks have inherent constraints concerning the best order in which to achieve the goals. A number of research efforts have been made to detect such constraints and to use them for guiding search, in the hope of speeding…

Artificial Intelligence · Computer Science 2011-07-04 J. Hoffmann , J. Porteous , L. Sebastia