While I have reported my research activities on this blog, as it would be difficult to find a thread going through them from the posts, I try to tidy them up and present remaining issues in this post.
Thematic summary
The aim of my research has been to understand human cognitive functions by implementing them (the synthetic approach) in a biologically plausible way. Since I have been interested in AGI, the functions of interest include fluid intelligence and language acquisition. While the overall purpose is to create a language learning agent, since it cannot be done at once, I made my implementation efforts in piecemeal fashion. To deal with the problem with compute and complication, I made the settings (environments) as simple as possible to avoid the need of pattern recognition, non-essential to the subject matters. In my efforts on fluid intelligence, I have been prioritizing architecture over learning, as it is about the architecture that enables to solve unseen tasks. Below I list articles I wrote by themes and in chronological order.
Researches on language acquisition
- 'Simulating the Usage Acquisition of Two-Word Sentences with a First- or Second-Person Subject and Verb' for BICA 2017.
An agent was implemented to learn language use by interacting with a 'caretaker' in a simple language and with social reward from the caretaker. - Implementation of a Parser without Grammar with Neural Sequence Memory
A blog post (2025) Note: almost all CFG parsers ever built are symbolic (i.e., not neural) and require hand-crafted explicit grammar. - A Language Model Grounded to a Simple Visual Environment with Active Vision (2025)
A blog post on the implementation
Researches on fluid intelligent
- Information Binding with Dynamic Associative Representations for a workshop at the AGI-13 conference (2013)
A conceptual paper claiming that information binding with neural networks can be realized by temporal associative traversing.
The idea was partly implemented in 2025: see the post above on the language model. - The Match-to-Sample Task as the First Milestone toward the Realization of Fluid Intelligence (2020)
A conceptual blog post on fluid intelligence (see Table 1 for the distinction between fluid intelligence and crystalized intelligence) - A Model of Fluid Intelligence based on Examining Experienced Sequences,
A conceptual blog post on rule/policy discovery (2022) - Solving a Delayed Match-to-Sample Task with Sequential Memory (2023)
An implementation of the previous post - Implementation of Neural Sequence Memory (2024)
A blog post - A Neural Model of Rule Discovery with Relatively Short-Term Sequence Memory (2024)
An arXiv article reporting an implementation of rule discovery with the neural sequence memory described in the previous post.
