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The 1995 Robot Competition and Exhibition - David P. Miller
The 1995 Robot Competition and Exhibition - David P. Miller

... UNM LOBOT is a custom-built mobile robot designed by UNM engineering students. The LOBOT is driven by a two-wheel differential configuration with supporting casters. It is octagonal in shape, stands about 75 centimeters tall, and measures about 60 centimeters in width. Sensing is achieved using a la ...
Increasing SIA  Architecture Realism by
Increasing SIA Architecture Realism by

... often seen in crisis situations. In other words, increased anxiety contributes to a particular situation assessment (e.g., aircraft is being attacked by hostile aircraft), which then limits the processing of data that could give rise to alternative interpretations and further increases the anxiety l ...
Neural Robot Detection in RoboCup
Neural Robot Detection in RoboCup

... After calculating the different features, they are passed to two artificial neural networks as can be seen in Figure 2. One network only processes the simple features, the input for the second one are the orientation histogram values. The breakdown into two networks turned out to be necessary in ord ...
events:knowledge-workshop-iros2011:tikanmaki.pdf (340.2 KB)
events:knowledge-workshop-iros2011:tikanmaki.pdf (340.2 KB)

... used for task planning, environment state progress prediction, etc. 2) Environment model An environment model forms a base for the robot’s task planning, navigation, obstacle avoidance, and for example human interaction. The model may also contain kinematic relations (like forces and masses), and it ...
ppt - LaDiSpe - Politecnico di Torino
ppt - LaDiSpe - Politecnico di Torino

... psychology arises from the brain & body physiology  Embodiment theory was introduced into AI by Rodney Brooks in the ‘80s. Brooks have claimed that all autonomous agents need to be both embodied and situated  The theory states that intelligent behavior emerges from the interplay between brain, bod ...
Cognitive Decathlon
Cognitive Decathlon

... In other cases, if the agent is being used to make predictive assessments of how a human would behave in a specific situation, verisimilitude would be a benefit as well. Finally, this criterion can provides some tests for how an agent processes information and reasons: for example, if one’s goal is ...
PPT
PPT

... world? • Single agent (vs. multi-agent): An agent operating by itself in an environment. Does the other agent interfere with my performance measure? ...
The Frankenstein Complex and Asimov`s Three Laws
The Frankenstein Complex and Asimov`s Three Laws

... There are still problems, however, even with this more specific set. For example, the Procreation Law, stating that a robot cannot take part in the creation of another robot not subject to the laws, is of the least priority – subordinate to even the fourth law stating that a robot has to follow its ...
How Robots Work
How Robots Work

... language and the ability to formulate original ideas. Roboticists are nowhere near achieving this level of artificial intelligence, but they have made a lot of progress with more limited AI. Today's AI machines can replicate some specific elements of intellectual ability. Computers can already solve ...
A conversation with a 3D face - Dipartimento di Informatica
A conversation with a 3D face - Dipartimento di Informatica

... questions; this opens a question-answering subdialog, after which Greta takes again the dialog control, by revising her discourse plan according to what occurred so far. As we said, we are particularly interested in simulating the ‘affective’ aspects of conversations; for this reason, we take medica ...
Stojanov
Stojanov

... Bickhard, which covers plethora of aspects related to mind and person. Within interactivism, an agent is regarded as an action system: an autonomous, selforganizing, self-maintaining entity, which can exercise actions and sense their effects in the environment it inhabits. In this paper, we will arg ...
A Comparative Study of Soft Computing Methodologies in
A Comparative Study of Soft Computing Methodologies in

... sulting in a hybrid system that both operates on linguistic descriptions of the variables and the numeric values through a parallel and fault tolerant architecture. The mapping properties of artificial neural networks have been analyzed by many researchers. Hornik [1], and Funahashi [2] have shown t ...
Humanoid Robots That Behave, Speak, and Think Like Humans: A
Humanoid Robots That Behave, Speak, and Think Like Humans: A

... Machine-like intelligence may refer to the objective knowledge programmed into all modern day computing devices. Human-like intelligence is obtained relative to the “self” of the machine. Human-like intelligence is called subjective knowledge. The following are six pre-requisites required to achieve ...
A Case Study in Developmental Robotics
A Case Study in Developmental Robotics

... a common one. For example, in an article (Barto et al., 1995) it was shown that majority of reinforcement learning (RL) algorithms are properly treated within the dynamic programming framework. RL methods which use dynamic programming as mathematical framework, require that environment be represente ...
Communications of the ACM
Communications of the ACM

... to manufacture a physical version of the evolved robot. Such an algorithm could, in principle, continually receive new desired behaviors and task environments and continuously generate novel robots. In this way, the roboticist can make fewer assumptions about the final form of the robot and have gre ...
Spoken dialogue technology achievements and challenges`` ( file)
Spoken dialogue technology achievements and challenges`` ( file)

... Examples of spoken dialogue systems Technical issues and challenges Future Prospects ...
A Behavior Analytic Paradigm for Adaptive Autonomous Agents
A Behavior Analytic Paradigm for Adaptive Autonomous Agents

... repeatedly placed in the target situations, and the agent's behaviors are observed. The consequences are delivered to the agent (if the environment does not deliver them automatically). Complexity of the learned behaviors is limited, however, due to the sheer number of interactions with the environm ...
I Agents, Bodies, Constraints, Dynamics, and Evolution Alan K. Mackworth
I Agents, Bodies, Constraints, Dynamics, and Evolution Alan K. Mackworth

... the opportunity to give the presidential address at AAAI-07 in Vancouver, my hometown. This article is based on that talk. That opportunity allowed me to step back and think of the big picture, the long perspective. The way to read the title, “Agents, Bodies, Constraints, Dynamics, and Evolution,” a ...
CptS 440 / 540 Artificial Intelligence
CptS 440 / 540 Artificial Intelligence

... Weak AI Position • Machines can be made to act as if they were intelligent – There are things that computers cannot do, no matter how we program them – Certain ways of designing intelligent programs are bound to fail in the long run – The task of constructing the appropriate programs ...
References
References

... Some issues and problems Natural environment v ability to control variables e.g. test in classroom v. bring into laboratory Interference with participants - ethical issues * Should you use a method of teaching that you do not think is going to work on your participants? * Should everyone get the op ...
Cooperative Mobile Robotics
Cooperative Mobile Robotics

... theories from such diverse disciplines as artificial intelligence, game theory/economics, theoretical biology, distributed computing/control, animal ethology and artificial life. ...
The AAAI 2006 Mobile Robot Competition and
The AAAI 2006 Mobile Robot Competition and

... (the difference in difficulty of the seven categories was accounted for by weighting each category with a predetermined factor). The audience interaction evaluation required conference attendees to interact with a robot and to fill out an evaluation form. The tasks were not tied to the seven categor ...
intelligent robots: the question of embodiment
intelligent robots: the question of embodiment

... increase the accuracy of strictly structured, exacting, and continuous quantifications, is not the only possibility. This may only provide a digital solution to an analogue problem, and consequently suffers from ever increasing complexity. Physical embodiment necessitates the use of approximate sol ...
A bayesian computer vision system for modeling human interactions
A bayesian computer vision system for modeling human interactions

... recursively in a Bayesian framework to fit real behavioral data. This approach provides a rather straightforward and flexible technique to the design of priors, one that does not require strong analytical assumptions to be made about the form of the priors.1 In our experiments, we have found that by ...
Comp 1017 Robots
Comp 1017 Robots

... Why learn to program with Robots ? 1. Robots are becoming commercially viable – need developers 2. Serious promise of Artificial Intelligence – needs researchers ...
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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.
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