Task analysis

About: Task analysis is a research topic. Over the lifetime, 10432 publications have been published within this topic receiving 283481 citations.

Decentralized planning for complex missions with dynamic communication constraints

Abstract: This paper extends the consensus-based bundle algorithm (CBBA), a distributed task allocation framework previously developed by the authors, to address complex missions for a team of heterogeneous agents in a dynamic environment. The extended algorithm proposes appropriate handling of time windows of validity for tasks, fuel costs of the vehicles, and heterogeneity in the agent capabilities, while preserving the robust convergence properties of the original algorithm. An architecture to facilitate real-time task replanning in a dynamic environment is also presented, along with methods to handle varying communication constraints and dynamic network topologies. Simulation results and experimental flight tests in an indoor test environment verify the proposed task planning methodology for complex missions.

Simultaneous cognitive operations in working memory after dual-task practice.

Abstract: The authors tested the hypothesis that with adequate practice, people can execute 2 cognitive operations in working memory simultaneously. In Experiment 1, 6 students practiced updating 2 items in working memory through 2 sequences of operations (1 numerical, 1 spatial). In different blocks, imperative stimuli for the 2 sequences of operations were presented either simultaneously or sequentially. Initially, most participants experienced substantial dual-task costs. After 24 sessions of practice, operation latencies for simultaneous presentation were equal to the maximum of times for the 2 operations in the sequential condition, suggesting perfect timesharing. Experiment 2 showed that a reduction of dual-task costs requires practice on the combination of the 2 updating tasks, not just practice on each individual task. Hence, the reduction of dual-task costs cannot be explained by shortening or automatization of individual operations.

Task Effects on Focus on Form in Synchronous Computer-Mediated Communication

Abstract: Previous research on synchronous computer-mediated communication (SCMC) has shown that SCMC interaction could draw learners' attention to form in ways that are similar to face-to-face interaction. However, the role of task type in focusing learners' attention on form has not been widely researched. In a repeated-measures design, this study investigated if task type had any effect on the number and characteristics of focus-on-form instances of 54 English-as-a-foreign-language learners. Two jigsaw-dictogloss task pairs were designed and matched for content. Following a practice task session, randomly formed dyads performed each of the tasks using MSN Messenger and CoWord software. Language-related episodes (LREs) were identified and categorized according to their focus, outcome, and type. Results showed that the dictogloss task elicited a higher number of LREs than the jigsaw task. Tasks also displayed some differences with respect to the characteristics of LREs. Whereas the dictogloss was characterized by orthographic, solved correctly, and negative feedback LREs, the jigsaw was characterized by unresolved LREs. The results are discussed in light of the arguments about the effects of limited information-processing capacity on task performance (). [ABSTRACT FROM AUTHOR]

Interactive Hierarchical Task Learning from a Single Demonstration

Abstract: We have developed learning and interaction algorithms to support a human teaching hierarchical task models to a robot using a single demonstration in the context of a mixedinitiative interaction with bi-directional communication. In particular, we have identified and implemented two important heuristics for suggesting task groupings based on the physical structure of the manipulated artifact and on the data flow between tasks. We have evaluated our algorithms with users in a simulated environment and shown both that the overall approach is usable and that the grouping suggestions significantly improve the learning and interaction. Categories and Subject Descriptors I.2.9 [Artificial Intelligence]: Robotics

Rethinking Task-Based Language Learning: What We Can Learn from the Learners.

Abstract: To investigate the use, or otherwise, of conversational adjustments (CAs), in a normal instructional setting, the quality of speech generated during meaning negotiation, and learner perception of t...