Re: KR for Cogai/gentle reminder

Hello,

Perhaps, Paola is referring to the theory in this book -> Brachman and
Levesque
<https://www.cin.ufpe.br/~mtcfa/files/in1122/Knowledge%20Representation%20and%20Reasoning.pdf>

Thanks,

Adeel

On Sat, 29 Oct 2022 at 03:06, Timothy Holborn <timothy.holborn@gmail.com>
wrote:

> Noted.
>
> https://en.wikipedia.org/wiki/Knowledge_representation_and_reasoning
>
> In terms of knowledge representation, for humanity, my thoughts have been
> that it's about the ability for people to represent the evidence of a
> circumstance in a court of law.  If solutions fail to support the ability
> to be used in these circumstances, to successfully represent knowledge -
> which can be relied upon in a court of law; a circumstance that should
> never be wanted, but desirable to support peace.
>
> Then, I guess, I'd be confused about the purposeful definion; or the
> useful purpose of any such tools being produced & it's relationship, by
> design, to concepts like natural justice.
>
> https://en.wikipedia.org/wiki/Natural_justice
>
> Let me know if I am actually "off topic" per the intended design outcomes.
>
> Regards,
>
> Timothy Holborn.
>
> On Sat, 29 Oct 2022, 11:55 am Paola Di Maio, <paoladimaio10@gmail.com>
> wrote:
>
>>
>> Just as a reminder, this list is about sharing knowledge, research and
>> practice in AI KR, The intersection with KR and CogAI may also be relevant
>> here (and of interest to me)
>>
>> If people want to discuss CogAI not in relation to KR, please use the
>> CogAI CG list?
>> What I mean is that: if KR is not of interest/relevance to a post, then
>> why post here?
>>
>> What is KR, its relevance and limitations is a vast topic, written about
>> in many scholarly books, but also these books are not adequately covering
>> the topic, In that sense, the topic of KR itself, without further
>> qualification, is too vast to be discussed without narrowing it down to a
>> specific problem/question
>> KR in relation to CogAI has been the subject of study for many of us for
>> many years, and it is difficult to discuss/comprehend/relate to for those
>> who do not share the background. I do not think this list can fill the huge
>> gap left by academia, however there are great books freely available online
>> that give some introduction .
>> When it comes to the application of KR to new prototypes, we need to
>> understand what these prototypes are doing, why and how. Unfortunately NN
>> fall short of general intelligence and intellegibility for humans.
>>
>> Adeel, thank you for sharing the paper 40 years of Cognitive Architectures
>> I am not sure you were on the list back then, but I distributed the
>> resource as a working reference for this list and anyone interested in
>> February 2021, and have used the resource as the basis for my research on
>> the intersection AI KR/CogAI since
>> https://lists.w3.org/Archives/Public/public-aikr/2021Feb/0017.html
>>
>> Dave: the topics KR, AI, CogAI and consciousness, replicability,
>> reliability, and all the issues brought up in the many posts in this thread
>> and other thread are too vast
>> to be discussed meaningfully in a single thread
>>
>> May I encourage the breaking down of topics/issues making sure the
>> perspective and focus of KR (including its limitations) are not lost in
>> the long threads
>>
>> Thank you
>> (Chair hat on)
>>
>> On Fri, Oct 28, 2022 at 6:23 PM Adeel <aahmad1811@gmail.com> wrote:
>>
>>> Hello,
>>>
>>> To start with might be useful to explore 'society of mind
>>> <http://aurellem.org/society-of-mind/index.html>' and 'soar' as point
>>> of extension.
>>>
>>> 40 years of cognitive architecture
>>> <https://link.springer.com/content/pdf/10.1007/s10462-018-9646-y.pdf>
>>>
>>> Recently, Project Debater
>>> <https://research.ibm.com/interactive/project-debater/> also came into
>>> the scene. Although, not quite as rigorous in Cog or KR.
>>>
>>> Thanks,
>>>
>>> Adeel
>>>
>>> On Fri, 28 Oct 2022 at 02:05, Paola Di Maio <paoladimaio10@gmail.com>
>>> wrote:
>>>
>>>> Thank you all for contributing to the discussion
>>>>
>>>> the topic is too vast - Dave I am not worried if we aree or not agree,
>>>> the universe is big enough
>>>>
>>>> To start with I am concerned whether we are talking about the same
>>>> thing altogether. The expression human level intelligence is often used to
>>>> describe tneural networks, but that is quite ridiculous comparison. If the
>>>> neural network is supposed to mimic human level intelligence, then we
>>>> should be able to ask; how many fingers do humans have?
>>>> But this machine is not designed to answer questions, nor to have this
>>>> level of knowledge about the human anatomy. A neural network is not AI in
>>>> that sense
>>>> it fetches some images and mixes them without any understanding of what
>>>> they are
>>>> and the process of what images it has used, why and what rationale was
>>>> followed for the mixing is not even described, its probabilistic. go figure.
>>>>
>>>> Hay, I am not trying to diminish the greatness of the creative neural
>>>> network, it is great work and it is great fun. But a) it si not an artist.
>>>> it does not create something from scratch b) it is not intelligent really,
>>>> honestly,. try to have a conversation with a nn
>>>>
>>>> This is what KR does: it helps us to understand what things are and how
>>>> they work
>>>> It also helps us to understand if something is passed for what it is
>>>> not *(evaluation)
>>>> This is is why even neural network require KR, because without it, we
>>>> don know what it is supposed
>>>> to do, why and how and whether it does what it is supposed to do
>>>>
>>>> they still have a role to play in some computation
>>>>
>>>> * DR Knowledge representation in neural networks is not transparent, *
>>>>> *PDM I d say that either is lacking or is completely random*
>>>>>
>>>>>
>>>>> DR Neural networks definitely capture knowledge as is evidenced by
>>>>> their capabilities, so I would disagree with you there.
>>>>>
>>>>
>>>> PDM  capturing knowledge is not knowledge representation, in AI,
>>>> capturing knowledge is only one step, the categorization of knowledge
>>>> is necessary to the reasoning
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>> *We are used to assessing human knowledge via examinations, and I
>>>>> don’t see why we can’t adapt this to assessing artificial minds *
>>>>> because assessments is very expensive, with varying degrees of
>>>>> effectiveness, require skills and a process -  may not be feasible when AI
>>>>> is embedded to test it/evaluate it
>>>>>
>>>>>
>>>>> We will develop the assessment framework as we evolve and depend upon
>>>>> AI systems. For instance, we would want to test a vision system to see if
>>>>> it can robustly perceive its target environment in a wide variety of
>>>>> conditions. We aren’t there yet for the vision systems in self-driving cars!
>>>>>
>>>>> Where I think we agree is that a level of transparency of reasoning is
>>>>> needed for systems that make decisions that we want to rely on.  Cognitive
>>>>> agents should be able to explain themselves in ways that make sense to
>>>>> their users, for instance, a self-driving car braked suddenly when it
>>>>> perceived a child to run out from behind a parked car.  We are less
>>>>> interested in the pixel processing involved, and more interested in whether
>>>>> the perception is robust, i.e. the car can reliably distinguish a real
>>>>> child from a piece of newspaper blowing across the road where the newspaper
>>>>> is showing a picture of a child.
>>>>>
>>>>> It would be a huge mistake to deploy AI when the assessment framework
>>>>> isn’t sufficiently mature.
>>>>>
>>>>> Best regards,
>>>>>
>>>>> Dave Raggett <dsr@w3.org>
>>>>>
>>>>>
>>>>>
>>>>>