Thanks very much for your question. For the thesis, I wrote an 'actual working program', described in chapters 5 and 6. Quoting from slides 24 & 25:
Chapter 5 presents the design for the prototype demonstration system, which I wrote in Jscheme and Java. Jscheme is a version of Scheme implemented in Java by Anderson, Hickey, and Norvig (2006).
The conceptual framework includes preliminary representations of perceived reality, semantic domains, mental spaces, conceptual blends, and event memory.
The prototype conceptual processes include executable concepts with pattern-matching, variable binding, transmission of mental speech acts between subagents, and composable grammatical constructions.
Chapter 6 discusses how the prototype illustrates that the TalaMind approach could potentially support the higher-level mentalities of human-level intelligence.
The demonstration illustrates learning and discovery by reasoning analogically, causal and purposive reasoning, meta-reasoning, imagination via nested conceptual simulation*, and internal dialog between subagents in a society of mind using a language of thought.
* Conceptual processing of hypothetical scenarios, with possible branching of scenarios based on alternative events, such as choices of simulated Tala agents within scenarios. “Nested” means that simulated agents can also perform this processing within hypothetical scenarios.The simulations show conceptual processing without encyclopedic and commonsense knowledge, and without a scalable, efficient architecture. These are needed to achieve human-level AI.
To avoid overstating (or understating) what the system does, I'd ask that people read chapters 5 and 6 for details. There are also some remarks related to design of the system in section 1.5.
I should say up front that the prototype system is very limited, and only performs predefined conceptual processing using Tala mentalese expressions. I do not claim to actually implement or achieve the higher-level mentalities. Within the scope of a Ph.D. effort, I could only try to show how they could in principle be supported using the thesis approach.
There are other places in this thread where the term "system" has been used more generally, in the abstract, discussing how a human-level AI system should work or be designed. I've been careful to only use the term "demonstration system" in reference to the system described above.
(links included for readers who may be new to the thread.)
> Subject: Re: [ontolog-forum] Toward Human-Level AI
> From: phayes@xxxxxxx
> Date: Sat, 31 May 2014 11:27:46 -0500
> CC: ontolog-forum@xxxxxxxxxxxxxxxx
> To: philipcjacksonjr@xxxxxxxxxxx
> Philip, greetings.
> Your emails and the references cited there make many references to a "system"; below, for example, you refer to a "demonstration system". Are you referring to an implementation of some kind, i.e. an actual running program? If so, can you give us some sketch of this system: what programming language you used, what task it performed, perhaps some details of its performance, etc..? If not, can you elucidate what exactly you mean by "system"?
> Pat Hayes
> On May 31, 2014, at 9:43 AM, Philip Jackson <philipcjacksonjr@xxxxxxxxxxx> wrote:
> > John,
> > Thanks very much for the excerpts from previous messages about language games. I agree with these excerpts, and about the importance of language games, and language being open-ended.
> > My thesis does not attempt to model or simulate language games directly. Rather, the demonstration system focuses on how use of a natural language mentalese can support "higher-level mentalities" (2.1.2) such as causal and purposive reasoning and learning, meta-reasoning, imagination, etc. I would agree that the ability to create and play language games should also be considered a higher-level mentality of human-level intelligence. (Incidentally, page 34 cites interesting research by Vogt (2005) on how perceptually grounded language games can lead to the emergence of compositional syntax in language evolution.)
> > Of course, I also agree that an intelligent system needs a KR language. As you noted earlier, my thesis argues for "the controversial claim that human-level AI is possible with a knowledge representation based on natural language". I think such a KR language is very important from a practical perspective in achieving human-level AI, though do not claim it's sufficient -- other forms of KR are also important, including formal logic KR's.
> > The thesis does not make claims about what goes on inside human brains, per se. Its focus is only on how computers could achieve human-level AI. Thus, while I think people probably also have a language of thought at least similar to natural language, the thesis does not argue for such a claim. Section 2.2.1 gives some background discussion related to this topic.
> > Phil
> > Thesis: http://www.philjackson.prohosting.com/PCJacksonPhDThesis20140422.pdf
> > Slides: http://www.philjackson.prohosting.com/TowardHumanLevelAI20140422.pdf
> > (links included for readers who may be new to the thread.)
> > > Date: Sat, 31 May 2014 09:10:49 -0400
> > > From: sowa@xxxxxxxxxxx
> > > To: ontolog-forum@xxxxxxxxxxxxxxxx
> > > Subject: Re: [ontolog-forum] Toward Human-Level AI
> > >
> > > Phil,
> > >
> > > > The mentalese I propose is not a language for formal logic, but a
> > > > language based on the syntax of a natural language, for representing
> > > > concepts normally expressed in natural language.
> > >
> > > For implementing an intelligent computer system, some KR language
> > > is necessary. The question of how that KRL is related to what goes
> > > on in the brain is another issue. Those issues are related, and
> > > it's interesting to study their relationships.
> > >
> > > But see below for slightly edited excerpts that I sent to a different
> > > email list on a related topic.
> > >
> > > John
> > > ___________________________________________________________________
> > >
> > > Email #1
> > > > since we've agreed, I believe, that we do not have any complete
> > > > and correct theory of any one human language
> > >
> > > Wittgenstein's later philosophy is not only consistent with that
> > > point, it has much stronger implications:
> > >
> > > 1. There is an open-ended infinity of language games that
> > > speakers play with the grammar and vocabulary of any language.
> > >
> > > 2. Every such game enriches, extends, and modifies the language.
> > > The simplest games merely add new senses or microsenses. But
> > > any game can also introduce new vocabulary and new grammar.
> > >
> > > Email #2
> > > > I would like to believe there are complete and correct theories
> > > > of some "professional languages"...
> > >
> > > No language is complete until it's dead. Physics is the hardest
> > > of the "hard sciences", but its basic terms -- mass, energy, force,
> > > momentum, electron, proton, gravity -- are constantly evolving.
> > >
> > > Engineers who apply physics always make approximations in their
> > > models, and they often use mutually inconsistent theories for
> > > different aspects of the same system.
> > >
> > > > ... at least in social and health care.
> > >
> > > That's an excellent example of the wide range of different
> > > "language games" with different microsenses by the many
> > > participants: surgeons, pharmacists, anesthesiologists,
> > > general practitioners, research physicians, nurses, hospital
> > > administrators, accountants, programmers, food preparers and
> > > servers, building maintenance, and -- of course -- patients.
> > >
> > > They all have to communicate, but they all speak different
> > > dialects with a considerable overlap of terms that they
> > > use and interpret in different microsenses -- even for
> > > a single patient for a single hospital admission.
> > >
> > >
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