Autonomous Agents Sample Clauses

Autonomous Agents. ‌ There are a lot of definitions of the term “agent” [62–66], because of the large variety of specific subclasses of agents based on different ideas, purposes, methods of reasoning about the world, etc. A widely used definition of an agent is proposed by Xxxxxxxxxx, Xxxxxxxx and Xxxxxx [63, 65, 66], and this definition is also used in our work. According to them, the main characteristics of an agent are autonomy, reactivity, pro-activeness and ability to socialize. Autonomy means the ability of an agent to make a decision without direct commands from humans or other agents. Reactivity is the ability of an agent to react to the changes of its environment in real-time. Pro-activeness denotes the ability to initiate the analysis of their intentions and plan according to the events occurred in the environment. Social ability means to cooperate and communicate with other agents to perform their own or common tasks. The last three characteristics are sometimes combined into one definition called flexibility [63]. Xxxxxxxxxx and Xxxxxxxx [65, 66] emphasise the social ability of the agents, arguing that agents should interact with each other to achieve the goal. Xxxxxx [64] distinguishes between hardware and software agents. Hardware agents are physical entities, which deal with the physical world using hardware components such as sensors and effectors. However, they use software components too (for instance, a physical robot is a hardware agent with a software control system [67]). Software agents are computer programs, which sense, act on and reason about a software “world”. Xxxxxxxx and Xxxxxxxx [62] point out the differences between software agents and non- agent programs. They insist that every software agent is represented by a program, but not every program represents an agent. The key differences lie in the autonomy of the agents and the way in which the agents interact with their environment. In comparison with non-agent programs, agents’ actions as its output affects its input, i.e. the agent can change the type and number of input parameters, according to its actions. In contrast, non-agent program cannot change the set of input parameters, according to its output. For example, an agent tries to find an appropriate flight, considering such parameters as destination, date and price. In this case, a non-agent program tries to search for the flight using all three parameters at once. The agent can find the list of flights to the appropriate destination, th...
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