Distributed artificial intelligence (DAI) also called Decentralized Artificial IntelligenceDemazeau, Yves, and J-P. Müller, eds. Decentralized Ai. Vol. 2. Elsevier, 1990. is a subfield of

artificial intelligence Artificial intelligence (AI) is the capability of computer, computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of re ...

research dedicated to the development of distributed solutions for problems. DAI is closely related to and a predecessor of the field of

multi-agent system A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents.H. Pan; M. Zahmatkesh; F. Rekabi-Bana; F. Arvin; J. HuT-STAR: Time-Optimal Swarm Trajectory Planning for Quadroto ...

s. Multi-agent systems and distributed problem solving are the two main DAI approaches. There are numerous applications and tools.

Definition

Distributed Artificial Intelligence (DAI) is an approach to solving complex learning,

planning Planning is the process of thinking regarding the activities required to achieve a desired goal. Planning is based on foresight, the fundamental capacity for mental time travel. Some researchers regard the evolution of forethought - the cap ...

, and decision-making problems. It is

embarrassingly parallel In parallel computing, an embarrassingly parallel workload or problem (also called embarrassingly parallelizable, perfectly parallel, delightfully parallel or pleasingly parallel) is one where little or no effort is needed to split the problem into ...

, thus able to exploit large scale computation and

spatial distribution A spatial distribution in statistics is the arrangement of a phenomenon across the Earth's surface and a graphical display of such an arrangement is an important tool in geographical and environmental statistics. A graphical display of a spatial ...

of computing resources. These properties allow it to solve problems that require the processing of very large

data set A data set (or dataset) is a collection of data. In the case of tabular data, a data set corresponds to one or more table (database), database tables, where every column (database), column of a table represents a particular Variable (computer sci ...

s. DAI systems consist of autonomous learning processing nodes ( agents), that are distributed, often at a very large scale. DAI nodes can act independently, and partial solutions are integrated by communication between nodes, often asynchronously. By virtue of their scale, DAI systems are robust and elastic, and by necessity, loosely coupled. Furthermore, DAI systems are built to be adaptive to changes in the problem definition or underlying data sets due to the scale and difficulty in redeployment. DAI systems do not require all the relevant data to be aggregated in a single location, in contrast to

monolithic A monolith is a monument or natural feature consisting of a single massive stone or rock. Monolith or monolithic may also refer to: Architecture * Monolithic architecture, a style of construction in which a building is carved, cast or excavated f ...

or centralized Artificial Intelligence systems which have tightly coupled and geographically close processing nodes. Therefore, DAI systems often operate on sub-samples or hashed impressions of very large datasets. In addition, the source dataset may change or be updated during the course of the execution of a DAI system.

Development

In 1975 distributed artificial intelligence emerged as a subfield of artificial intelligence that dealt with interactions of intelligent agents. Distributed artificial intelligence systems were conceived as a group of intelligent entities, called agents, that interacted by cooperation, by coexistence or by competition. DAI is categorized into multi-agent systems and distributed problem solving. In

s the main focus is how agents coordinate their knowledge and activities. For distributed problem solving the major focus is how the problem is decomposed and the solutions are synthesized.

Goals

The objectives of Distributed Artificial Intelligence are to solve the

reasoning Reason is the capacity of consciously applying logic by drawing valid conclusions from new or existing information, with the aim of seeking the truth. It is associated with such characteristically human activities as philosophy, religion, scien ...

, planning, learning and perception problems of

, especially if they require large data, by distributing the problem to autonomous processing nodes (agents). To reach the objective, DAI requires: * A

distributed system Distributed computing is a field of computer science that studies distributed systems, defined as computer systems whose inter-communicating components are located on different networked computers. The components of a distributed system commun ...

with robust and elastic computation on unreliable and failing resources that are loosely coupled * Coordination of the actions and communication of the nodes * Subsamples of large data sets and

online machine learning In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques whic ...

There are many reasons for wanting to distribute intelligence or cope with multi-agent systems. Mainstream problems in DAI research include the following: * Parallel problem solving: mainly deals with how classic artificial intelligence concepts can be modified, so that

multiprocessor Multiprocessing (MP) is the use of two or more central processing units (CPUs) within a single computer system. The term also refers to the ability of a system to support more than one processor or the ability to allocate tasks between them. The ...

systems and clusters of computers can be used to speed up calculation. * Distributed

problem solving Problem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business an ...

(DPS): the concept of

agent Agent may refer to: Espionage, investigation, and law *, spies or intelligence officers * Law of agency, laws involving a person authorized to act on behalf of another ** Agent of record, a person with a contractual agreement with an insuran ...

, autonomous entities that can communicate with each other, was developed to serve as an

abstraction Abstraction is a process where general rules and concepts are derived from the use and classifying of specific examples, literal (reality, real or Abstract and concrete, concrete) signifiers, first principles, or other methods. "An abstraction" ...

for developing DPS systems. See below for further details. * Multi-Agent Based Simulation (MABS): a branch of DAI that builds the foundation for simulations that need to analyze not only phenomena at macro level but also at

micro Micro may refer to: Measurement * micro- (μ), a metric prefix denoting a factor of 10−6 Places * Micro, North Carolina, town in U.S. People * DJ Micro, (born Michael Marsicano) an American trance DJ and producer * Chii Tomiya (都宮 � ...

level, as it is in many social simulation scenarios.

Approaches

Two types of DAI has emerged: * In

Multi-agent system A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents.H. Pan; M. Zahmatkesh; F. Rekabi-Bana; F. Arvin; J. HuT-STAR: Time-Optimal Swarm Trajectory Planning for Quadroto ...

s agents coordinate their knowledge and activities and reason about the processes of coordination. Agents are physical or virtual entities that can act, perceive its environment and communicate with other agents. The agent is autonomous and has skills to achieve goals. The agents change the state of their environment by their actions. There are a number of different coordination techniques. * In distributed problem solving the work is divided among nodes and the knowledge is shared. The main concerns are task decomposition and synthesis of the knowledge and solutions. DAI can apply a bottom-up approach to AI, similar to the

subsumption 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.Brooks, R. A., "A Robust Pro ...

as well as the traditional top-down approach of AI. In addition, DAI can also be a vehicle for

emergence In philosophy, systems theory, science, and art, emergence occurs when a complex entity has properties or behaviors that its parts do not have on their own, and emerge only when they interact in a wider whole. Emergence plays a central rol ...

Challenges

The challenges in Distributed AI are: # How to carry out communication and interaction of agents and which communication language or protocols should be used. # How to ensure the coherency of agents. # How to synthesise the results among 'intelligent agents' group by formulation, description, decomposition and allocation.

Applications and tools

Areas where DAI have been applied are: *

Electronic commerce E-commerce (electronic commerce) refers to Commerce, commercial activities including the electronic buying or selling Goods and services, products and services which are conducted on online platforms or over the Internet. E-commerce draws on tec ...

, e.g. for trading strategies the DAI system learns financial trading rules from subsamples of very large samples of financial data *

Networks Network, networking and networked may refer to: Science and technology * Network theory, the study of graphs as a representation of relations between discrete objects * Network science, an academic field that studies complex networks Mathematics ...

, e.g. in

telecommunications Telecommunication, often used in its plural form or abbreviated as telecom, is the transmission of information over a distance using electronic means, typically through cables, radio waves, or other communication technologies. These means of ...

the DAI system controls the cooperative resources in a

WLAN A wireless LAN (WLAN) is a wireless computer network that links two or more devices using wireless communication to form a local area network (LAN) within a limited area such as a home, school, computer laboratory, campus, or office buildin ...

network *

Routing Routing is the process of selecting a path for traffic in a Network theory, network or between or across multiple networks. Broadly, routing is performed in many types of networks, including circuit-switched networks, such as the public switched ...

, e.g. model vehicle flow in transport networks *

Scheduling A schedule (, ) or a timetable, as a basic time-management tool, consists of a list of times at which possible tasks, events, or actions are intended to take place, or of a sequence of events in the chronological order in which such things ...

, e.g. flow shop scheduling where the

resource management In organizational studies, resource management is the efficient and effective development of an organization's resources when they are needed. Such resources may include the financial resources, inventory, human skills, production resources, or ...

entity ensures local optimization and cooperation for global and local consistency *

Search engines Search engines, including web search engines, selection-based search engines, metasearch engines, desktop search tools, and web portals and vertical market websites have a search facility for online databases. By content/topic Gene ...

, e.g. in LLM

federated search Federated search retrieves information from a variety of sources via a search application built on top of one or more search engines. A user makes a single query request which is distributed to the search engines, databases or other query engines ...

like Ithy where document retrieval and analysis are distributed to DAI agents before aggregation * Multi-Agent systems, e.g.

artificial life Artificial life (ALife or A-Life) is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry. The discipline ...

, the study of simulated life * Electric power systems, e.g. Condition Monitoring Multi-Agent System (COMMAS) applied to transformer condition monitoring, and IntelliTEAM II Automatic Restoration System DAI integration in tools has included: * ECStar is a distributed rule-based learning system.

Agents

Systems: Agents and multi-agents

Notion of Agents: Agents can be described as distinct entities with standard boundaries and interfaces designed for problem solving. Notion of Multi-Agents: Multi-Agent system is defined as a network of agents which are loosely coupled working as a single entity like society for problem solving that an individual agent cannot solve.

Software agents

The key concept used in DPS and MABS is the abstraction called

software agent In computer science, a software agent is a computer program that acts for a user or another program in a relationship of agency. The term ''agent'' is derived from the Latin ''agere'' (to do): an agreement to act on one's behalf. Such "action on ...

s. An agent is a virtual (or physical)

autonomous In developmental psychology and moral, political, and bioethical philosophy, autonomy is the capacity to make an informed, uncoerced decision. Autonomous organizations or institutions are independent or self-governing. Autonomy can also be defi ...

entity that has an understanding of its environment and acts upon it. An agent is usually able to communicate with other agents in the same system to achieve a common goal, that one agent alone could not achieve. This communication system uses an

agent communication language Agent Communication Language (ACL), are computer communication protocols that are intended for AI Agents to communication with each other. During the 2007, protocols of this nature were proposed which include: * FIPA-ACL (by the Foundation for In ...

. A first classification that is useful is to divide agents into: * reactive agent – A reactive agent is not much more than an automaton that receives input, processes it and produces an output. * deliberative agent – A

deliberative agent Deliberative agent (also known as intentional agent) is a sort of software agent used mainly in Multi-agent system, multi-agent system simulations. According to Wooldridge's definition, a deliberative agent is "one that possesses an explicitly repr ...

in contrast should have an internal view of its environment and is able to follow its own plans. * hybrid agent – A hybrid agent is a mixture of reactive and deliberative, that follows its own plans, but also sometimes directly reacts to external events without deliberation. Well-recognized agent architectures that describe how an agent is internally structured are: * ASMO (emergence of distributed modules) * BDI (Believe Desire Intention, a general architecture that describes how plans are made) * InterRAP (A three-layer architecture, with a reactive, a deliberative and a social layer) * PECS (Physics, Emotion, Cognition, Social, describes how those four parts influences the agents behavior). * Soar (a rule-based approach)