Intelligently designed clinical studies

Negotiating Intelligently

The predominant approaches to automating competitive interaction appeal to the central notion of a utility function that represents an agent’s preferences. Agent’s are then endowed with machinery that enables them to perform actions that are intended to optimise their expected utility. Despite the extent of this work, the deployment of automatic negotiating agents in real world scenarios is rar...

Intelligently Choosing Testing Techniques

Inspecting and ASSERTing Intelligently

Software testability is a misunderstood technology by most of the software test ing community Most testing experts believe that software testability is either a measure of complexity or a subjective assessment of how much it will cost to gen erate test cases perform coverage testing write drivers and or stubs etc This perspective is incomplete In the late s an alternative perspective on testa b...

Responding Intelligently to Unparsable Inputs

All natural language systems are likely to receive inputs for which they are unprepared. The system must be able to respond to such inputs by explicitly indicating the reasons the input could not be understood, so that the user will have precise information for trying to rephrase the input. If natural language communication to data bases, to expert consultant systems, or to any other practical ...

Aligning Ontologies Intelligently

In the semantic web, ontology plays an important role to provide formal definitions of concepts and relationships. Due to the presence of several similar ontologies in the same domain, there might be several definitions for a given concept. Ontology alignment overcomes these difficulties by exploring a map between similar entities that refer to the same concept in two different ontologies. This...