Using Cognitive Agents to Train Negotiation Skills

Using Cognitive Agents to Train Negotiation Skills

Training negotiation is difficult because it is a complex, dynamic activity that involves multiple parties. It is often not clear how to create situations in which students can practice negotiation or how to measure students' progress. Some have begun to address these issues by creating artificial software agents with which students can train. These agents have the advantage that they can be "r...

Learning from Stories: Using Natural Communication to Train Believable Agents

In this work we introduce Quixote, a system that allows non-programmers to train believable virtual agents and robots using the sociocultural knowledge present in stories. Quixote uses a corpus of exemplar stories to engineer a reward function that can be used to train virtual agents to exhibit desired behaviors using reinforcement learning. We show the effectiveness of our system with a case s...

Using the Wizard of Oz Method to Train Persuasive Agents

Learning From Stories: Using Crowdsourced Narratives to Train Virtual Agents

In this work we introduce Quixote, a system that makes programming virtual agents more accessible to nonprogrammers by enabling these agents to be trained using the sociocultural knowledge present in stories. Quixote uses a corpus of exemplar stories to automatically engineer a reward function that is used to train virtual agents to exhibit desired behaviors using reinforcement learning. We sho...

Concurrent Negotiation using Software Agents in Cloud

In today’s cloud environment, multiple service providers are available; among these most favorable service should be allocated to consumers as per their requirement. By introducing software agents, consumer and the provider are negotiating with each other to meet the requirement. The exactly favorable market discovered using cloud ontology, which gives the similarities between consumer services...