Context and background:
SingularityNET Foundation, in collaboration with other partners such as the OpenCog Foundation and TrueAGI, is working toward a scalable implementation of the Hyperon AGI framework running on decentralized infrastructure, and toward implementation of the PRIMUS cognitive architecture within this framework.
OpenCog Hyperon involves multiple algorithms and components, which need to demonstrate appropriate functionalities both individually and in combination. This RFP aims to address a portion of this overall need, via funding the initial iteration of one significant component of OpenCog Hyperon.
A crucial component of cognitive synergy is a system for allocating attention to Atoms in the Distributed Atomspace (DAS) in order to efficiently allocate system resources. The goal of this project is to create a framework for evaluating different Attention Allocation (AA) approaches by assessing their dynamics within Hyperon.
In addition to cognitive components like PLN and MOSES, the framework should also consider how attentional processes operate within systems that incorporate neural networks. Given that neural networks introduce sub-symbolic processing dynamics, it will be important to explore how AA can manage resources between symbolic systems (e.g., PLN, MOSES) and neural architectures. Attentional dynamics in hybrid symbolic-neural systems must be considered for their efficiency, adaptability, and relevance in complex problem-solving scenarios.
Possible questions to ask in constructing such a measurement framework could include:
- What quantity or quantities should we measure?
- How should such measures react to environmental changes?
- What sorts of attention dynamics would be desired?
- How do we align measure(s) with desired dynamics?
- Others?
Below we provide information about AA approaches and measurements previously constructed within OpenCog Classic. In this RFP, we are open to new and creative ideas to better assess AA dynamics within Hyperon. In this sense, the RFP is quite wide open.
The Economic Attention Networks (ECAN) module (https://agi-conf.org/2009/papers/paper_63.pdf) fulfilled the AA role within OpenCog Classic. As demonstrated in (https://www.researchgate.net/publication/304459082_Controlling_Combinatorial_Explosion_in_Inference_via_Synergy_with_Nonlinear-Dynamical_Attention_Allocation) and https://www.researchgate.net/publication/383696770_Using_Nonlinear_Dynamical_Attention_Allocation_to_Focus_Probabilistic_Logical_Inference_Upon_Relevant_Information#fullTextFileContent
ECAN effectively selected relevant premises for the Probabilistic Logic Networks (PLN) uncertain inference system to perform reasoning upon and come to better conclusions, within the context of OpenCog Classic.
What is needed for OpenCog Hyperon is a similar, but perhaps broader, system able to measure AA cognitive dynamics across the entire PRIMUS cognitive architecture including PLN and evolutionary methods such as the Meta-Optimizing Semantic Evolutionary Search (MOSES) procedural learning algorithm (https://www.cs.york.ac.uk/rts/docs/GECCO_2007/docs/p626.pdf).
However, in order to develop and evaluate various approaches to creating such a “similar, but perhaps broader” system, it will be valuable to have a systematic framework for evaluating attention allocation approaches in a Hyperon and PRIMUS context.
Collaboration:
This RFP may be followed by subsequent RFPs for applications that leverage Hyperon/PRIMUS to carry out various applications, and that aim to guide Hyperon/PRIMUS systems in cognitive development toward beneficial AGI.
RFP Expected Outcomes:
- Primary outcome would be a framework in which to evaluate various approaches to AA. Some possible ideas to include and questions to address in creation of the framework are:
- To attempt to solve the smokes test problem, or other similar realistic problems that could be used to evaluate AA effectiveness on PLN
- Application to simplistic game world interactions.
- A demonstration of how AA benefits evolutionary methods such as MOSES
- Consideration of how AA could aid AI-DSL service composition
- Potentially better ways to assess AA dynamics within Hyperon
- The OC Classic ECAN system helps PLN pick better premises via the Attentional Focus based upon short-term importance values – Are there additional or different items we wish to measure?
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