A Symbiotic Cognitive Computing Perspective on Autonomic Computing

Kephart, Jeffrey O.; Lenchner, Jonathan

doi:10.1109/icac.2015.16

Cited by 21 publications

(13 citation statements)

References 11 publications

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“…The demonstration begins with two humans discussing the CEL environment, followed by one agent describing a projection of the Mind of Mr.Jones on the screen. The other agent then discusses how a Mergers and Acquisitions (M&A) task [7] is carried out.…”

Section: Engagementioning

confidence: 99%

“…Previous work on such assistive agents has included both purely software agents [4,5] as well as ones that co-inhabit physical spaces with humans [6] and use their understanding of what is happening in those spaces to act as collaborators on cognitive tasks such as decision making. CELIA -the Cognitive Environments Laboratory Interactive Agent -is an early prototype of such an agent in an embodied environment called the CEL [7]. While CELIA in its present form has been used for hundreds of customer engagements and decision-intensive settings [8], by and large the style of interaction has been command-response; i.e.…”

Section: Introductionmentioning

confidence: 99%

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Planning and visualization for a smart meeting room assistant1

Chakraborti

Fadnis

Talamadupula

et al. 2019

AIC

Self Cite

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In this paper, we report on the planning and visualization capabilities of Mr.Jones -a proactive orchestrator and decision-support agent for a collaborative decision making setting embodied by a smart room. The duties of such an agent may range across interactive problem solving with other agents in the environment, developing automated summaries of meetings, visualization of the internal decision-making process, proactive data and resource management, and so on. Specifically, we focus on how the visualization of the planning and plan recognition processes forms a key component of the smart assistant, and establishes transparency in the decision-making process. We also highlight how these processes contribute to the proactive nature of the agent. We demonstrate some of these functionalities in a successful deployment of the system in the CEL -the Cognitive Environments Laboratory at IBM's T.J. Watson Research Center (Yorktown, USA), and report on emerging deployments of the system that have turned into success stories.

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Section: Engagementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Planning and visualization for a smart meeting room assistant1

Chakraborti

Fadnis

Talamadupula

et al. 2019

AIC

Self Cite

View full text Add to dashboard Cite

show abstract

“…They built a Cognitive Environments Laboratory (CEL) to explore how people and cognitive computing implementations work together [30,31]. The CEL approach sees the role of the computer as a "super expert", which interacts with people, offering advice and information based on superior computational power.…”

Section: Related Workmentioning

confidence: 99%

Strong Cognitive Symbiosis: Cognitive Computing for Humans

Veres

2017

BDCC

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"Cognitive Computing" has become somewhat of a rallying call in the technology world, with the promise of new smart services offered by industry giants like IBM and Microsoft. The associated technological advances in Artificial Intelligence (AI) have thrown into the public sphere some old questions about the relationship between machine computation and human intelligence. Much of the industry and media hype suggests that many traditional challenges have been overcome. On the contrary, our simple examples from language processing demonstrate that present day cognitive computing still struggles with fundamental, long-standing problems in AI. An alternative interpretation of cognitive computing is presented, following Licklider's lead in adopting "man-computer symbiosis" as a metaphor for designing software systems that enhance human cognitive performance. A survey of existing proposals on this view suggests a distinction between weak and strong versions of symbiosis. We propose a Strong Cognitive Symbiosis, which dictates an interdependence rather than simply cooperation between human and machine functioning, and introduce new software systems, which were designed for cognitive symbiosis. We conclude that strong symbiosis presents a viable new perspective for the design of cognitive computing systems.

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“…Their methods introduce error in 10% of tested web pages in order to simplify the viewing of all on mobile screens. As in our work, Kephart and Lenchner focus on online data-intensive computations occurring across multiple components working together [23]. While we measure the answer quality of online system responses, their work displays interpreted system responses to the user and corrects computations when the user indicates incorrect analysis.…”

Section: Related Workmentioning

confidence: 99%

Measuring and Managing Answer Quality for Online Data-Intensive Services

Kelley

Stewart

Morris

et al. 2015

2015 IEEE International Conference on Autonomic Computing

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Abstract-Online data-intensive services parallelize query execution across distributed software components. Interactive response time is a priority, so online query executions return answers without waiting for slow running components to finish. However, data from these slow components could lead to better answers. We propose Ubora, an approach to measure the effect of slow running components on the quality of answers. Ubora randomly samples online queries and executes them twice. The first execution elides data from slow components and provides fast online answers; the second execution waits for all components to complete. Ubora uses memoization to speed up mature executions by replaying network messages exchanged between components. Our systems-level implementation works for a wide range of platforms, including Hadoop/Yarn, Apache Lucene, the EasyRec Recommendation Engine, and the OpenEphyra question answering system. Ubora computes answer quality much faster than competing approaches that do not use memoization. With Ubora, we show that answer quality can and should be used to guide online admission control. Our adaptive controller processed 37% more queries than a competing controller guided by the rate of timeouts.

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A Symbiotic Cognitive Computing Perspective on Autonomic Computing

Cited by 21 publications

References 11 publications

Planning and visualization for a smart meeting room assistant1

Planning and visualization for a smart meeting room assistant1

Strong Cognitive Symbiosis: Cognitive Computing for Humans

Measuring and Managing Answer Quality for Online Data-Intensive Services

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