Topic- and mode-sensitive interaction strategies : Functions of ellipsis in oral communication

In this article, we discuss ellipsis as an interactive strategy by analysing the author’s textchat corpus and the VOICE corpus of English as a Lingua Franca. It is found that there were fewer repetitions in the textchat data, and this is explained as a consequence of the textchat mode. Textchat contributions are preserved as long as the chat is active or has been saved, and therefore users can scroll through and review the discussion, compared to the more fleeting nature of oral conversation. As a result, repetition is less necessary. The frequency of other functions identified could be attributed to the topic of discourse. Discussions involve much ellipsis used to develop discourse, although some were self-presentations with repetition used to confirm details. Back-channel support and comments were often low because speakers instead used forms like yeah as supportive utterances.

Interaction among agents that plan

The development of practical agent languages has progressed significantly over recent years, but this has largely been independent of distinct developments in aspects of multiagent cooperation and planning. For example, while the popular AgentSpeak(L) has had various extensions and improvements proposed, it still essentially a single-agent language. In response, in this paper, we describe a simple, yet effective, technique for multiagent planning that enables an agent to take advantage of cooperating agents in a society. In particular, we build on a technique that enables new plans to be added to a plan library through the invocation of an external planning component, and extend it to include the construction of plans involving the chaining of subplans of others. Our mechanism makes use of plan patterns that insulate the planning process from the resulting distributed aspects of plan execution through local proxy plans that encode information about the preconditions and effects of the external plans provided by agents willing to cooperate. In this way, we allow an agent to discover new ways of achieving its goals through local planning and the delegation of tasks for execution by others, allowing it to overcome individual limitations.