China
Africa
Explore chapters and articles related to this topic
Embodied AI, or the tale of taming the fungus eater
Published in Arkapravo Bhaumik, From AI to Robotics, 2018
Autonomy loosely would mean that no other entity is required to feed its input nor is any required to keep it running. The robots can sense and act to fulfill given and implied goals in a dynamic environment, and they can go on working without any external intervention for substantially long periods of time. Franklin and Graesser [111] suggest the following definition for autonomous agents: “An autonomous agent is a system situated within and a part of an environment that senses that environment and acts on it, over time, in pursuit of its own agenda and so as to effect what it senses in the future.”
Virtual Environments
Published in Julie A. Jacko, The Human–Computer Interaction Handbook, 2012
Kay M. Stanney, Joseph V. Cohn
Autonomous agents are synthetic or virtual human entities that possess some degree of autonomy, social ability, reactivity, and proactiveness (Allbeck and Badler 2002). There are several types of agents (Serenko and Detlor 2004), including user agents (i.e., assist users by interacting with them, knowing their preferences and interests, and acting on their behalf), service agents (i.e., seamlessly collaborate with different parts of a system and perform more general tasks in the background, unbeknownst to users), embedded agents (i.e., interact with user and system to hide task complexity and make the overall user experience more exciting and enjoyable), and stand-alone agents (i.e., employ leading-edge technologies and lay down the foundation for new architectures, standards, and innovative formats of agent-based computing). Autonomous agents can have many forms (e.g., human, animal), which are rendered at various levels of detail and style, from cartoonish to physiologically accurate models; the form of the agent has been found to influence behavior both during and post VE exposure (i.e., the Proteus Effect, where people infer their expected behaviors and attitudes from observing the appearance of their avatar; Yee, Bailenson, and Ducheneaut [2009]). Such agents are a key component of many VE applications involving interaction with other entities, such as adversaries, instructors, or partners (Stanney and Zyda 2002). Considerable work is being done to enhance the believability of such agents. For example, Heylen et al. (2008) found that when human–like eye gaze behavior was incorporated into agents, users communicated with such agents more effectively, and of utmost importance, human performance was also found to be enhanced with the more life-like agents. As our understanding of how best to design autonomous agents evolves, such principles will be important to incorporate into their design to enhance the overall engagement and effectiveness of virtual worlds.
Intelligent Agent Technology
Published in Jay Liebowitz, The Handbook of Applied Expert Systems, 2019
David Prerau, Mark R. Adler, Dhiraj K. Pathak, Alan Gunderson
Agents that modify their behavior over time to adapt to their environment are viewed as intelligent autonomous agents. Research in this area is concerned with developing autonomous agents that can improve their performance over time, or “learn” to adapt to their changing environment.
RPMInter-work: a multi-agent approach for planning the task-role assignments in inter-organisational workflow
Published in Enterprise Information Systems, 2020
Meriam Jemel, Nadia Ben Azzouna, Khaled Ghedira
In (Jennings and Wooldridge 1998), an agent is defined as: ”a computer system situated in some environment, and that is capable of autonomous action in this environment in order to meet its design objectives.” An autonomous agent should be able to act without the direct intervention of humans (or other agents), and should have control over its own actions and internal state. In a Multi-Agent System (MAS), agents communicate with each other in a system to reach common goals. Integration of workflow and agent technology has attracted a lot of attention of researchers in the related areas. In fact, traditional workflow systems have certain limitations such as replying on central control, lack of reactivity, semantics, resource management and interoperation. Facing these problems, intelligent agent paradigm is among the technologies that can benefit the workflow technology (Jennings and Wooldridge 1998; Jennings et al. 2000). Indeed, Agent-based workflow provided distributed system architecture, easy interaction, resource management, reactivity to changes, interoperation among heterogeneous systems, and intelligent decision-making.
Building trust with voice assistants for apparel shopping: The effects of social role and user autonomy
Published in Journal of Global Fashion Marketing, 2023
Jennifer Huh, Claire Whang, Hye-Young Kim
Voice assistants are often referred to as autonomous agents as they can take the initiative to accomplish goals and communicate with other entities (Wooldridge, 1999). However, the VA’s intelligent ability to complete the tasks autonomously made consumers display concerns over adopting it. Experts also warn that infringement of autonomy is a major barrier to their adoption (De Bellis and Venkataramani Johar 2020). Subsequently, researchers call for a study examining consumers’ perception of autonomy when interacting with VAs.