Related Research Articles
In software engineering, multitier architecture or multilayered architecture is a client–server architecture in which presentation, application processing, and data management functions are physically separated. The most widespread use of multitier architecture is the three-tier architecture.
Subsumption architecture is a reactive robotic architecture heavily associated with behavior-based robotics which was very popular in the 1980s and 90s. The term was introduced by Rodney Brooks and colleagues in 1986. Subsumption has been widely influential in autonomous robotics and elsewhere in real-time AI.
Distributed Artificial Intelligence (DAI) also called Decentralized Artificial Intelligence is a subfield of artificial intelligence research dedicated to the development of distributed solutions for problems. DAI is closely related to and a predecessor of the field of Multi-Agent Systems.
Soar is a cognitive architecture, originally created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University. It is now maintained and developed by John Laird's research group at the University of Michigan.
Business process automation (BPA), also known as business automation or digital transformation, is the technology-enabled automation of complex business processes. It can streamline a business for simplicity, achieve digital transformation, increase service quality, improve service delivery or contain costs. It consists of integrating applications, restructuring labor resources and using software applications throughout the organization. Robotic process automation is an emerging field within BPA and uses artificial intelligence.
In robotics, a robotic paradigm is a mental model of how a robot operates. A robotic paradigm can be described by the relationship between the three primitives of robotics: Sense Plan Act. It can also be described by how sensory data is processed and distributed through the system, and where decisions are made.
Action selection is a way of characterizing the most basic problem of intelligent systems: what to do next. In artificial intelligence and computational cognitive science, "the action selection problem" is typically associated with intelligent agents and animats—artificial systems that exhibit complex behaviour in an agent environment. The term is also sometimes used in ethology or animal behavior.
In artificial intelligence, reactive planning denotes a group of techniques for action selection by autonomous agents. These techniques differ from classical planning in two aspects. First, they operate in a timely fashion and hence can cope with highly dynamic and unpredictable environments. Second, they compute just one next action in every instant, based on the current context. Reactive planners often exploit reactive plans, which are stored structures describing the agent's priorities and behaviour.
Modular self-reconfiguring robotic systems or self-reconfigurable modular robots are autonomous kinematic machines with variable morphology. Beyond conventional actuation, sensing and control typically found in fixed-morphology robots, self-reconfiguring robots are also able to deliberately change their own shape by rearranging the connectivity of their parts, in order to adapt to new circumstances, perform new tasks, or recover from damage.
In artificial intelligence, a procedural reasoning system (PRS) is a framework for constructing real-time reasoning systems that can perform complex tasks in dynamic environments. It is based on the notion of a rational agent or intelligent agent using the belief–desire–intention software model.
A hierarchical control system is a form of control system in which a set of devices and governing software is arranged in a hierarchical tree. When the links in the tree are implemented by a computer network, then that hierarchical control system is also a form of networked control system.
Ronald Craig Arkin is an American roboticist and roboethicist, and a Regents' Professor in the School of Interactive Computing, College of Computing at the Georgia Institute of Technology. He is known for the motor schema technique in robot navigation and for his book Behavior-Based Robotics.
The Autonomous Robot Architecture (AuRA) is a hybrid deliberative/reactive robot architecture developed by Ronald C. Arkin at the Georgia Institute of Technology. It was developed in mid-1980's. AuRA is one of the first Hybrid Robotic Architecture developed. Hybrid Robotic Architecture forms form combination of reactive and deliberative approaches and gets best from both the approaches.
The Distributed architecture for mobile navigation (DAMN) is a mobile robot architecture developed by Julio K. Rosenblatt at Carnegie Mellon University. DAMN consists of a collection of independently operating behaviors such as "go-to-goal" and "avoid obstacle", and an arbiter. The arbiter generates a set of feasible action possibilities for the robot over a short time horizon, and the behaviours vote on these candidate actions. Votes may be weighted by a mode manager. The Pareto optimal action is then sent to the vehicle controller. One method of obtaining votes is for behaviours to asynchronously update a utility map over the configuration space of the robot. The arbiter then overlays paths resulting from action candidates onto the map, and samples utilities along the paths. This approach is known as utility fusion. In DAMN, the decision-making process is distributed and asynchronous, without the need for an hierarchical structure.
The Servo, subsumption, and symbolic (SSS) architecture is a hybrid reactive/deliberative robot architecture developed by Jonathan H. Connell the IBM T.J. Watson Research Center.
Allen was a robot introduced by Rodney Brooks and his team in the late 1980s, and was their first robot based on subsumption architecture. It had sonar distance and odometry on board, and used an offboard lisp machine to simulate subsumption architecture. It resembled a footstool on wheels.
In artificial intelligence research, the situated approach builds agents that are designed to behave effectively successfully in their environment. This requires designing AI "from the bottom-up" by focussing on the basic perceptual and motor skills required to survive. The situated approach gives a much lower priority to abstract reasoning or problem-solving skills.
Deliberative agent is a sort of software agent used mainly in multi-agent system simulations. According to Wooldridge's definition, a deliberative agent is "one that possesses an explicitly represented, symbolic model of the world, and in which decisions are made via symbolic reasoning".
A Behavior Tree (BT) is a mathematical model of plan execution used in computer science, robotics, control systems and video games. They describe switchings between a finite set of tasks in a modular fashion. Their strength comes from their ability to create very complex tasks composed of simple tasks, without worrying how the simple tasks are implemented. BTs present some similarities to hierarchical state machines with the key difference that the main building block of a behavior is a task rather than a state. Its ease of human understanding make BTs less error prone and very popular in the game developer community. BTs have been shown to generalize several other control architectures.
References
- ↑ Firby, R.J. (1990). Adaptive Execution in Complex Dynamic Worlds.
- ↑ Gat, E.; Others, (1998). "On three-layer architectures" (PDF). Artificial Intelligence and Mobile Robots: 195–210. Retrieved 2008-04-06.