Real world applications as in industry and robotics need modelling rich and
diverse automated planning problems. Their resolution usually requires
coordinated and concurrent action execution. In several cases, these problems
are naturally decomposed in a hierarchical way and expressed by a Hierarchical
Task Network (HTN) formalism.
HDDL, a hierarchical extension of the Planning Domain Definition Language
(PDDL), unlike PDDL 2.1 does not allow to represent planning problems with
numerical and temporal constraints, which are essential for real world
applications. We propose to fill the gap between HDDL and these operational
needs and to extend HDDL by taking inspiration from PDDL 2.1 in order to
express numerical and temporal expressions. This paper opens discussions on the
semantics and the syntax needed for a future HDDL 2.1 extension.

本文探讨了如何通过从 PDDL 2.1 中汲取灵感以表示数字和时间表达式，来扩展 HDDL，从而填补 HDDL 在实际应用中缺少数字和时间约束的问题。

HDDL 2.1：面向时态 HTN 规划定义形式与语义

HDDL 2.1: Towards Defining a Formalism and a Semantics for Temporal HTN  Planning

CASP is an extension of ASP that allows for numerical constraints to be added
in the rules. PDDL+ is an extension of the PDDL standard language of automated
planning for modeling mixed discrete-continuous dynamics.
In this paper, we present CASP solutions for dealing with PDDL+ problems,
i.e., encoding from PDDL+ to CASP, and extensions to the algorithm of the EZCSP
CASP solver in order to solve CASP programs arising from PDDL+ domains. An
experimental analysis, performed on well-known linear and non-linear variants
of PDDL+ domains, involving various configurations of the EZCSP solver, other
CASP solvers, and PDDL+ planners, shows the viability of our solution.

论文介绍了 CASP 扩展 ASP 的功能，能够处理规则中的数字约束。PDDL + 是用于模拟离散和连续混合动力学的自动计划 PDDL 标准语言的扩展。研究人员提出了 CASP 解决方案，以解决来自 PDDL + 领域的 CASP 程序，并在知名的 PDDL + 领域的线性和非线性变体上进行了实验分析，表明他们的解决方案可行。

混合领域规划的 CASP 解决方案

CASP Solutions for Planning in Hybrid Domains

We present the CIFF proof procedure for abductive logic programming with
constraints, and we prove its correctness. CIFF is an extension of the IFF
proof procedure for abductive logic programming, relaxing the original
restrictions over variable quantification (allowedness conditions) and
incorporating a constraint solver to deal with numerical constraints as in
constraint logic programming. Finally, we describe the CIFF system, comparing
it with state of the art abductive systems and answer set solvers and showing
how to use it to program some applications. (To appear in Theory and Practice
of Logic Programming - TPLP).

本文介绍了 CIFF 证明过程，证明了它的正确性，它是 IF 证明过程的扩展，用于处理带有数量约束的突发逻辑编程问题，同时介绍了 CIFF 系统，与最先进的突发系统和答案集求解器进行比较，并展示了如何使用它来编程一些应用程序。