Several Roles of Autonomous Agents
Autonomous agents are decentralized e-work networks adopted to respond to expanding complexity and dynamicity of E-Systems. They can process and undertake instructions given or learned in a restricted domain. Autonomous agents react to the environment on behalf of the users (Nof et al., 2015). The autonomous agents have healthcare, telecommunication, transportation, and supply network design applications.
Autonomous agents are applied in healthcare for patient monitoring. Healthcare professionals around the globe can interact with each other to perform specific tasks. For instance, clinicians can cooperate and exchange knowledge in the Surgical Intensive Care Unit. Different levels of doctors and nurses can collaborate to perform the medical function through autonomous agents effectively. Action agents, reasoning agents, and control agents are the levels of cooperation in a hierarchy from the lowest to the highest, respectively. Autonomous agents tackle healthcare challenges by facilitating the cooperation of experts from different states.
Telecommunication handle complex interactions that bear increasing inconsistency rate and hence require autonomous agents. Autonomous agents act as act to negotiate the increasing aspects of telecommunication elements such as caller-ID services. The shipment of imported goods also requires autonomous agents to locate storage and organize sub-plans and global plans. Additionally, several autonomous agents build a malleable search algorithm in multiple destination routing to provide the information of different routes in a supply network.
How They Enable Effective Collaboration
An agent-based system allows homogeneous and/or heterogeneous agents to collaborate with individual attributes. Determined coordination mechanisms are therefore necessary for the effective Collaboration of agents. Agents collaborate to achieve common goals in either decentralized or centralized models of task regulation. Several aspects have been developed to enable optimum Collaboration within a collaborative network of enterprises.
Communication and coordination between two agents establish effective collaboration. Communication can be improved by enhancing and monitoring the requests and responses between different agents. Individual agents represent production facilities or retail locations optimized with estimated demands. Efficient data transmission mechanism by facilitating comprehensive integration in the central server and access points improve communication and hence collaboration of agents. Communication makes different agents a collaborative supply network through effective communication to guarantee order fulfillment.
Learning the behaviors of real ant systems improves collaboration between agents. An agent can be classified as either a buyer or seller and the deal depends on the offer between the opponents. Behavior analysis develops the best matching aspects where different agents can be matched with respective users of E-Systems. The demand and the capacity sharing proposals are therefore perfectly matched. An artificial ant is assigned to capacity sharing proposals and navigates through different nodes, representing demand sharing proposals (Nof et al., 2015). The ant’s capacity and demand of the nodes also determine the paths to be selected hence appropriate cooperation. Integrated Process Planning and Scheduling IPPS tackle challenges of selecting and scheduling processes for easy operations in a collaborative agency.
Illustration for the E-Work Example
An Intelligent Agent is an e-work example that performs autonomous functions and improves collaborations. IA commands artificial intelligence to perform various functions through evaluated decisions. IA’s can perform functions on behalf of the users and sense the environment. For instance, IA can detect differences between caller ID services in telecommunications. Collaboration between users and providers in agent development is crucial when developing an intelligent agent. IA is, therefore, an autonomous agency that conducts the duties of users or programs after sensing the environment.
Reference
Nof, S. Y., Ceroni, J., Jeong, W., & Moghaddam, M. (2015). Optimization and Control. Revolutionizing Collaboration through e-Work, e-Business, and e-Service, 115-165.