Dale A. Lambert

High Level Information Fusion (HLIF): Survey of models, issues, and grand challenges

High-level information fusion (situation and threat assessment, process and user refinement) requires novel solutions for the operational transition of information fusion designs. Low-level (signal processing, object state estimation and characterization) is well-vetted in the community as compared to high-level information fusion (control and relationships to the environment). Specific areas of interest include modeling (situations, environments), representations (semantic, knowledge, and complex), information management (ontologies, protocols) systems design (scenario-based, user-based, distributed-agent) and evaluation (measures of performance/effectiveness, and empirical case studies).

Grand challenges of information fusion

The paper presents the Future Operations Centre Analysis Laboratory data34sion system, composed of both people and machines, A WDL revision of the JDL model of data fusion is proposed for this data fusion system. This leads to the identification of a number of grand challenges of information fusion. The Future Operations Centre Analysis Laboratory programme approach to these grand challenges is also discussed.

A blueprint for higher-level fusion systems

This paper contends that demands on the data fusion community are beginning to exceed its historical roots in sensor fusion, by requiring greater development of automated situation and impact assessments and more appropriate integration with humans engaged in fusion activity. The paper offers a seven building block blueprint for the design of higher-level fusion systems. The first building block involves a deconstruction of the JDL model to apply it beyond machine based fusion. The second addresses machine representation for automated situation and impact assessments, while the third examines machine reasoning for automated situation and impact assessments. The fourth building block then reconstructs a unified framework for automated object, situation and impact assessments so as to accommodate both of the previous building blocks and the traditional approach to sensor fusion. Distributed data fusion constitutes the subsequent building block. The automated presentation of automated situation and impact assessments serves as the sixth building block, before the issue of human involvement in higher-level fusion systems is canvassed. Existing implementations of the various building blocks are referenced rather than discussed in any detail. The aim of the paper is to expose the overarching framework for these higher-level fusion systems without recourse to their considerable underlying complexity.

High Level Information Fusion developments, issues, and grand challenges: Fusion 2010 panel discussion

The goal of the High-Level Information Fusion (HLIF) Panel Discussion is to present contemporary HLIF advances and developments to determine unsolved grand challenges and issues. The discussion will address the issues between low-level (signal processing and object state estimation and characterization) and high-level information fusion (control, situational understanding, and relationships to the environment). Specific areas of interest include modeling (situations, environments), representations (semantic, knowledge, and complex), systems design (scenario-based, user-based, distributed-agent) and evaluation (measures of effectiveness and empirical case studies). The goal is to address the contemporary operational and strategic issues in information fusion system design.

A distributed agent approach to global transportation scheduling

A suitable method for distributed transportation scheduling is necessary for the development of an agent-based logistics support system for the Australian Defence Force. Manager Agents (MA) require resources to be transported, in large quantities and on a global scale, using the services of many transport agents (TA). We investigate the application of K. Fischer et al.s (1996) Extended Contract Net Protocol (ECNP) to our transportation domain. ECNP provides a distributed and reactive approach to transportation scheduling that is fairly suited to this domain, but has its shortfalls. This includes the inability for TA to bid for partial routes, in addition to partial quantities, for a transportation task. A new protocol is proposed, based on ECNP, called the Provisional Agreement Protocol (PAP), which overcomes these shortfalls. Five speech acts, together with policies regarding the persistence and commitment of tasks and bids, are proposed. This allows agents to revisit bid options that were previously selected, and thus accomodates bidding for partial routes.

Distributed information fusion agents

Information fusion is typically data driven and applied to adversarial contexts. Advantages of a goal driven fusion process are emerging. An agent approach to fusion applied to friendly contexts, such as logistics, is presented. Agents are suitable for fusion because they can represent autonomous fusion eritities by modelling their capabilities, expertise and intentions. This paper promotes a level 3 centric view of information fusion, and focuses on impact and situation fusion. Extended Contract Net Protocol (ECNP) provides a distributed fusion approach, but has its shortfalls for the fusion domain. Provisional Agreement Prorocol (PAP) is an extension of the ECNP. It allows backtracking and a deliberative approach to fusion. Details of PAP are presented.

STDF model based maritime situation assessments

The state transition data fusion (STDF) model is an extension of the dominant sensor fusion paradigm to provide a unification of both sensor and higher-level fusion. Maritime domain awareness (MDA) is the problem of situation awareness in the maritime domain. This paper outlines an application of the STDF model to perform automated situation assessments for an aspect of MDA.

Automating cognitive routines

The paper contends that a symbolic approach to higher-level machine data /usion is required. This induces an Epistemic Challenge that is arguably best addressed through a combination o/ cognitive and analytic approaches. A cognitive model, a process /or cognitive capture, and a computational framework /or automating captured cognitive routines, are outlined.

Provisional agreement protocol for global transportation scheduling

The global transportation scheduling problem is complex, decentralised, open and dynamic. It typically requires the services of many transport organizations to transport partial quantities along partial routes to fulfill a transportation task. We have applied agents to address this problem. The Provisional Agreement Protocol (PAP) was developed to facilitate the planning required in our transportation problem. A greedy PAP approach has been implemented for the complex global transportation problem, allowing partial quantity and route bids, and backtracking if an infeasible solution is encountered. In this paper, we present the PAP, together with some improvements over that which has been previously presented. Further implementation details and formal evaluation are provided. Our implementation allows a wider range of transportation problems to be solved than previous approaches.

From single static to multiple dynamic combinatorial auctions

We apply the provisional agreement protocol (PAP) as a new approach to single static, single dynamic and multiple combinatorial auction problems, and empirically evaluate PAP. PAP benefits over one-shot auctions include: bidders not required to submit all bids and their dependencies; interaction with a changing environment during the auction can improve the solution; less communication when each bidder possesses many bids. PAPs backtracking may allow a better solution to be found than the first (greedy) solution, but can be detrimental with multiple auctions when bids (resources) are limited. With multiple auctions, dynamics and competition increases as resources becomes scarce. Therefore, PAP is likely to perform better when many resources are available, which is when auctions are useful anyway. PAP scales well, and applying PAP to a second domain shows its generality.