• Study Resource
  • Explore
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
A Review of Case-Based Reasoning in Cognition
A Review of Case-Based Reasoning in Cognition

... that similar problems are likely to have similar solutions, which can be used to solve new similar problems. Two key indicators of CBR are context-sensitive representations coupling a concrete problem situation with a corresponding solution, and similarity-based search for reusable cases. Besides a ...
Blackwell Guide to the Philosophy of Computing and
Blackwell Guide to the Philosophy of Computing and

... through computational models. Despite these similarities, there is an important difference between the modeling strategies artificial intelligence and artificial life typically employ. Most traditional AI models are top-down-specified serial systems involving a complicated, centralized controller th ...
Advances in conversational case-based reasoning
Advances in conversational case-based reasoning

... In many case-based reasoning (CBR) applications, a complete description of the target problem is assumed to be available in advance. This is an unrealistic assumption in domains such as interactive fault diagnosis, where it is natural for users to provide only a brief initial description of the prob ...
Robotics - Krupa Vara Prasad Adimulapu
Robotics - Krupa Vara Prasad Adimulapu

... systems for their control, sensory feedback, and information processing. The design of a given robotic system will often incorporate principles of mechanical engineering, electronic engineering, and computer science (particularly artificial intelligence). The study of biological systems often plays ...
Searching Social Networks
Searching Social Networks

... who have the desired information or expertise. Finding them involves naturally depends on our social network: our friends, our friends’ friends, and so on. Clearly, building and maintaining a central repository of social relationships is not feasible: people usually cannot and, because of considerat ...
PDF file
PDF file

... machine, which executes the task. Therefore, two phases are involved: the developmental phase and the performance phase, as illustrated in Fig. 2. In the developmental phase, a human engineer accepts a task that the machine is supposed to perform. He understands and analyzes the task before construc ...
Improving Adjustable Autonomy Strategies for Time
Improving Adjustable Autonomy Strategies for Time

... Actions - The arrows in Figure 2 represent the actions that enable state transitions. However, now in the RIAACT model, much like the real world, actions do not take a fixed amount of time. Instead, each arrow also has a corresponding function which maps time to probability of completion at that poi ...
Goal-Based Action Priors - Humans to Robots Laboratory
Goal-Based Action Priors - Humans to Robots Laboratory

... the agent prefers immediate rewards over future rewards (the agent prefers to maximize immediate rewards as γ decreases). MDPs may also include terminal states that cause all action to cease once reached (such as in goal-directed tasks). Goal-based action priors build on Object-Oriented MDPs (OO-MDP ...
Bodley_wsu_0251E_11404 - Washington State University
Bodley_wsu_0251E_11404 - Washington State University

... work beginning as early as ten years ago, this dissertation never would have been possible. Dr. Thoma helped show me that strong voices should be encouraged, no matter how quiet they may seem. From Mr. Apperson I was reminded that the fantastic imagination in science fiction generates real science a ...
From Natural Language to Soft Computing: New Paradigms
From Natural Language to Soft Computing: New Paradigms

... The most important objective reached during the workshop is that it opened the way for an interdisciplinary collaboration between researchers in different countries (Romania, USA, France, Serbia, Chile, Greece and Hungary), with different professional experience (scientific researchers, doctors and ...
Siri, a Virtual Personal Assistant Bringing Intelligence to the Interface
Siri, a Virtual Personal Assistant Bringing Intelligence to the Interface

... control relevant task parameters, leave “tedious” details to underlying levels of control ...
cs.cmu.edu - Stanford Artificial Intelligence Laboratory
cs.cmu.edu - Stanford Artificial Intelligence Laboratory

... is how to assign tasks to individual robots and and best coordinate their behaviours. In loosely coupled domains, much success in task allocation has been achieved with both auction based approaches ([1], [2]) and behaviour based robotics ([3], [4]). For more tightly coupled domains in which robots ...
ppt
ppt

... What comes first? ...
Housekeeping with Multiple Autonomous Robots: Representation
Housekeeping with Multiple Autonomous Robots: Representation

... and a chair and the passage between the table and the chair is too narrow for the robot to pass through. • When a plan execution fails, the robots may need to find another plan by taking into account some temporal constraints. For instance, when a robot cannot move an object because it is heavy, the ...
Affordances for robots: a brief survey
Affordances for robots: a brief survey

... planning system; this intermediate ‘buffer’ can potentially become a disconnect between the real state of the environment and the agent’s beliefs. Second ly, plan failure is treated as an exception that is usually hand led by explicit re-planning. With the uncertainty and unpredictability inherent i ...
A Neural Schema Architecture for Autonomous Robots
A Neural Schema Architecture for Autonomous Robots

... involving adaptation and learning, sophisticated software architectures are required. The neural schema architecture provides such a system, supporting the development and execution of complex behaviors, or schemas [3][2], in a hierarchical and layered fashion [9] integrating with neural network pro ...
affordance - Aleksandra Derra
affordance - Aleksandra Derra

... A more recent formalization of this viewpoint is formulated by Şahin et al. (2007) and Ugur et al. (2009). They begin their formalization of affordances by observing that a specific interaction with the environment can be represented by a relation of the form (effect, (entity, behavior)), where the ...
Aalborg Universitet The Meaning of Action
Aalborg Universitet The Meaning of Action

... 2. understand what effects certain actions have on the environment of the actor (recognizing the action by observing its effects on the environment) 3. understand how to physically perform a certain action in order to cause a particular change in the environment. While the first two points are commo ...
Matching Conflicts:  Functional Validation  of  Agents
Matching Conflicts: Functional Validation of Agents

... on. The same is true of linear system solvers, other numerical algorithms and data products. In some complicated computationtasks, the possible situations are more challenging. For example, there are manydifferent system modeling algorithms developed for different control systems such as ARMX or ARM ...
Future Computing and Robotics: A Report from the HBP Foresight Lab
Future Computing and Robotics: A Report from the HBP Foresight Lab

... the organizations and institutions of our modern world are now widely recognised. Power stations, industry, urban food distribution, economic markets, our schools, hospitals, transportation networks, communication systems, and police, civil and military defence infrastructure are all in some way org ...
word office version - European Parliament
word office version - European Parliament

... contractual terms, conclude contracts and decide whether and how to implement them make the traditional rules inapplicable, which highlights the need for new, efficient and up-to-date ones, which should comply with the technological development and the innovations recently arisen and used on the mar ...
Human-Robot-Communication and Machine Learning
Human-Robot-Communication and Machine Learning

... for deciding what to do next. They call their approach plan as communication (Agre and Chapman, 1990). Instead of de ning a sequence of xed and deterministic operators, plans just help to decide what's good to reach a given goal. Therefore, interpreting and executing a plan is more complex than in ...
The Evolution of Self-Esteem. In M. Kernis
The Evolution of Self-Esteem. In M. Kernis

... domains of same-sex dyadic alliances, coalitions, and kinships. Where self-assessed traits will be relevant to multiple adaptive domains, invoking entirely separate self-assessment mechanisms for each domain of self-esteem both lacks parsimony and entails postulating the existence of costly redundan ...
Strategic Planning for Unreal Tournament© Bots
Strategic Planning for Unreal Tournament© Bots

... Bots must react to an ever-changing environment. We advocate the use of HTN planning techniques to accomplish the goals of formulating a grand strategy and assigning tasks for the individual Bots to accomplish this strategy. At the same time we retain the event-driven programming of each individual ...
Part 2 - Simon Fraser University
Part 2 - Simon Fraser University

... Limitations of reactive architectures • But also some drawbacks: – Agents must be able to map local knowledge to appropriate action – Impossible to take non-local (or long-term) information into account – If it works, how do we know why it works? The departure from “knowledge level” implies a loss ...
< 1 2 3 4 5 6 ... 19 >

Adaptive collaborative control

Adaptive collaborative control is the decision-making approach used in hybrid models consisting of finite-state machines with functional models as subcomponents to simulate behavior of systems formed through the partnerships of multiple agents for the execution of tasks and the development of work products. The term “collaborative control” originated from work developed in the late 90’s and early 2000 by Fong, Thorpe, and Baur (1999). It is important to note that according to Fong et al. in order for robots to function in collaborative control, they must be self-reliant, aware, and adaptive. In literature, the adjective “adaptive” is not always shown but is noted in the official sense as it is an important element of collaborative control. The adaptation of traditional applications of control theory in teleoperations sought initially to reduce the sovereignty of “humans as controllers/robots as tools” and had humans and robots working as peers, collaborating to perform tasks and to achieve common goals. Early implementations of adaptive collaborative control centered on vehicle teleoperation. Recent uses of adaptive collaborative control cover training, analysis, and engineering applications in teleoperations between humans and multiple robots, multiple robots collaborating among themselves, unmanned vehicle control, and fault tolerant controller design.Like traditional control methodologies, adaptive collaborative control takes inputs into the system and regulates the output based on a predefined set of rules. The difference is that those rules or constraints only apply to the higher-level strategy (goals and tasks) set by humans. Lower tactical level decisions are more adaptive, flexible, and accommodating to varying levels of autonomy, interaction and agent (human and/or robotic) capabilities. Models under this methodology may query sources in the event there is some uncertainty in a task that affects the overarching strategy. That interaction will produce an alternative course of action if it provides more certainty in support of the overarching strategy. If not or there is no response, the model will continue performing as originally anticipated.Several important considerations are necessary for the implementation of adaptive collaborative control for simulation. As discussed earlier, data is provided from multiple collaborators to perform necessary tasks. This basic function requires data fusion on behalf of the model and potentially a need to set a prioritization scheme for handling continuous streaming of recommendations. The degree of autonomy of the robot in the case of human-robot interaction and weighting of decisional authority in robot-robot interaction are important for the control architecture. The design of interfaces is an important human system integration consideration that must be addressed. Due to the inherent varied interpretational scheme in humans, it becomes an important design factor to ensure the robot(s) are correctly conveying its message when interacting with humans.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report