while learners’ ability to speak academic language develops over time in content-based programs, the development of their nonacademic language appears to lag behind. students’ speaking in content-based (cb) classrooms is confined to an academic discourse style. in the researchers’ point of view, the gap of less amount of nonacademic speaking can be bridged by the application of the conceptual f...

We discuss a general framework for coordinating self-interested agents in the pre-planning phase that can be used to decompose multi-agent task based planning problems into independent subproblems. The decomposition allows the agents to solve their part of the problem without the need to interact with other agents and such that the resulting plans can be easily combined into a joint plan. We il...

An important area in AI Planning is the expressiveness of planning domain specification languages such as PDDL, and their aptitude for modelling real applications. This paper presents OCLplus, an extension of a hierarchical object centred planning domain definition language, intended to support the representation of domains with continuous change. The main extension in OCLplus provides the capa...

The field of deterministic AI planning can roughly be divided into two approaches — classical statebased planning and hierarchical task network (HTN) planning. The plan existence problem of the former is known to be decidable while it has been proved undecidable for the latter. When extending HTN planning by allowing the unrestricted insertion of tasks and ordering constraints, one obtains a fo...

Hybrid Planning combines Hierarchical Task Network (HTN) planning with concepts known from Partial-Order Causal-Link (POCL) planning. We introduce novel heuristics for Hybrid Planning that estimate the number of necessary modifications to turn a partial plan into a solution. These estimates are based on the task decomposition graph that contains all decompositions of the abstract tasks in the p...

AI Planning & Scheduling techniques are being widely used to adapt learning paths to the special features and needs of students both in distance learning and lifelong learning environments. However, instructors strongly rely on Planning & Scheduling experts to encode and review the domains for the planner/scheduler to work. This paper presents an approach to automatically extract a fully operat...

Interaction with users is a key capability of planning systems that are applied in real-world settings. Such a system has to be able to react appropriately to requests issued by its users. Most of these systems are based on a generated plan that is continually criticised by him, resulting in a mixed-initiative planning system. We present several practically relevant requests to change a plan in...

Classical planning is the problem of synthesizing a sequence of actions to reach the goal state starting from the initial state. Hierarchical task networks (HTNs) have been used as a guidance for solving planning problems where tasks are decomposed into subtasks. Recently, both action-based planning as well as HTNbased planning have been east as SAT. The performance of planning as SAT has been ...

This paper describes a collaboration between two PhD students. The first author is developing a course generator (CG) for a Web-based e-learning environments (WBLE) [3]. A CG generates sequences of learning objects according to the learner’s goals and individual properties. The assembling process is knowledge intensive: assembling courses that implement modern pedagogical theories requires a fr...

Considerable work has focused on enhancing the semantics of Hierarchical Task Networks (HTNs) in order to advance the state-of-the-art in hierarchical planning. For instance, the Hierarchical Goal Network (HGN) formalism operates over a hierarchy of goals to facilitate tighter integration of decompositional planning with classical planning. Another example is the Action Notation Markup Language...