What's the difference between those two representations of a planning problem?
Grounded representation restricts the planning rules to propositional logic: no variables, simple condition => effect rules.
Lifted representation extends this to simple FOPC (first-order predicate calculus), in which you get variables, predicates (straightforward status functions), and simple operations (such as negation).
Is that enough of a partition for your purposes?
Related
For my university task I must design a Deterministic Finite Automata which recognises basic arithmetic. We're basically building a very basic lexical analyzer.
The DFA uses the operators "+,-,*,/".
The DFA has only positive numbers so expressions like "-1+1","+1+1" aren't accepted.
It can accept decimals but only when they start with 0. so "0.3415" is accepted while "1.3415" is not.
Finally it can accept just a "0" by itself.
I'm confused about the best way to approach this. I have a basic foundation of DFAs and NFAs so can someone please just give me some hints as to how I should start?
My current approach is to draw some small DFAs. One for decimal numbers, one for whole numbers, one for operators, and one that's just a 0. Then I want to concatenate them and do the union of the smaller DFAs to create one big NFA and end it by converting back to a DFA.
Why is this goal not considered safe?
MANAGER(Name) :- WORKER(Name, Age, _ ), ¬ SUBORDINATE (_, Name), Age <= 40
Our teacher says that it is because SUBORDINATE is negate, and so it can not have undefined (_) spaces, but it seems to be logic for me this expression.
Anyone that can help me?
The safety requirements in Datalog are intended to prevent infinite results. If you have a variable that occurs in the head and only negated in the body, then it can be bound to infinitely many values, which would obviously be a problem.
The specific requirements for safety are hard to precisely formulate, so usually you see the requirements simplified to 'every variable has to occur positively'. This is a bit more restrictive than needed.
The most informative answer to the question would be that the rule is technically unsafe, but that it does not have an infinite result. Some Datalog engines would allows this rule and return the finite result.
This rule is perfectly safe and it does not produce an infinite relation. It is an implementation deficiency of the Datalog engine you are using.
In general, an easy way to handle _ is to convert it into a fresh variable. This makes the implementation of the engine easy, but probably is the reason why this clause throws an error. If it was a variable, there would be an infinite number of values SUBORDINATE's first parameter cannot be.
Please explain the differences about Traditional and Fuzzy Logics(FLS).
It will help understand about those systems to beginners(Like me).
Fuzzy Logic (FL) is a method of reasoning that resembles human reasoning. The approach of FL imitates the way of decision making in humans that involves all intermediate possibilities between digital values YES and NO.
The conventional logic block that a computer can understand takes precise input and produces a definite output as TRUE or FALSE, which is equivalent to a human’s YES or NO.
Traditional logic: a system of formal logic mainly concerned with the syllogistic forms of deduction that is based on Aristotle and includes some of the changes and elaborations made by the Stoics and the Scholastics: Aristotelian logic — compare immediate inference, opposition, subject-predicate, syllogism, symbolic logic
FOR MORE INFO ABOUT THE FUZZY lOGIC SEE THIS :
https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_fuzzy_logic_systems.htm
I hope that I could help you to understand the difference.
Not sure if this is within the realm of SO but:
Using VDM-SL, I have been looking around for the 'best' way of describing a single, finite subset of ℕ. In my travels I have found several ways that people are conveying this but I wonder which is the most accepted.
I initially thought that F(ℕ) would do but I believe that this is the set of finite subsets of ℕ, rather than a single subset.
Would it be enough to say, "Let S be finite: S ⊂ ℕ?"
Or does such a notation exist?
All sets in VDM language are finite by definition, so I believe there is no need to explicitly specify that part. As defined here http://wiki.overturetool.org/images/c/cb/VDM10_lang_manV2.pdf section 3.2.1
Now, to model a type which is a subset of a set s2 , one of the ways is to use an invariant on that type. such as "inv t == s1 subset s2".
I am struggling a bit with the meaning of determinism and nondeterminism. I get the difference when it comes to automata, but I can't seem to find an answer for the following: Is a NFA to DFA transformation deterministic?
If multiple DFAs can be constructed for the same regular language, does that mean that the result of a NFA to DFA transformation is not unique? And thus a nondeterministic algorithm?
I'm happy with any information you guys might be able to provide.
Thanks in advance!
There are two different concepts at play here. First, you are correct that there can be many different DFAs equivalent to the same NFA, just as there can be many NFAs that are all equivalent to one another.
Independently, there are several algorithms for converting an NFA into a DFA. The standard algorithm taught in most introductory classes on formal languages is the subset construction (also called the powerset construction). That algorithm is deterministic - there's a specific sequence of steps to follow to convert an NFA to a DFA, and accordingly you'll always get back the same DFA whenever you feed in the same NFA. You could conceivably have a nondeterministic algorithm for converting an NFA to a DFA, where the algorithm might produce one of many different DFAs as output, but to the best of my knowledge there aren't any famous algorithms of this sort.
Hope this helps!
DFA- means deterministic finite automata
Where as NFA- means non deterministic finite automata..
In dfa for every state there is a transition for both the inputs... I we have...{a, b} are the inputs for the given question.. For.. Every state there is a transition for both a and b... That automata is known as deterministic finite automata..
Where as in NDA we need not to have both input transitions for every state... At least one transition... is sufficient...
In NFA Epsilon transition is also accepted.. And dead state is also accepted...
In nfa... No of states required is less.. When compare to dfa.. Every dfa is equivalent to nfa... But every dfa is not equivalent to nfa...