scholarly journals THE n-r.e. DEGREES: UNDECIDABILITY AND Σ1 SUBSTRUCTURES

2012 ◽  
Vol 12 (01) ◽  
pp. 1250005 ◽  
Author(s):  
MINGZHONG CAI ◽  
RICHARD A. SHORE ◽  
THEODORE A. SLAMAN

We study the global properties of [Formula: see text], the Turing degrees of the n-r.e. sets. In Theorem 1.5, we show that the first order of [Formula: see text] is not decidable. In Theorem 1.6, we show that for any two n and m with n < m, [Formula: see text] is not a Σ1-substructure of [Formula: see text].

2002 ◽  
Vol 124 (4) ◽  
pp. 179-189 ◽  
Author(s):  
Joa˜o Paulo J. Matsuura ◽  
Michael M. Bernitsas ◽  
Luis O. Garza-Rios ◽  
Kazuo Nishimoto

Various hydrodynamic maneuvering models are available for modeling the slow motion horizontal plane dynamics of mooring and towing systems. In previous work, we compared four representative and widely used maneuvering models and assessed them based on the design methodology for mooring systems developed at the University of Michigan. In this paper, we study the impact of experimental uncertainties in the maneuvering coefficients on mooring system dynamic analysis. Uncertainties in higher order coefficients may even result in sign change as measured by different experimental facilities. This may indicate lack of robustness in maneuvering modeling. In our recent work, maneuvering models were classified in two schools of thought, each having a different set of coefficients subject to uncertainties. The first school is represented by the Abkowitz (A-M) and the Takashina (T-M) models, and the second by the Obokata (O-M) and the Short Wing (SW-M) models. The design methodology developed at the University of Michigan uses time independent global properties of mooring system dynamics to compare the maneuvering models, and assess their sensitivity and robustness. Equilibria, bifurcation sequences and associated morphogeneses, singularities of bifurcations, and secondary equilibrium paths are such global properties. Systematic change of important coefficients in each model shows that, for both schools of thought, sensitivity to first order terms is high while sensitivity to higher order terms is low. Accuracy in measurement of first order terms is high while accuracy in measurement of higher order terms is low. These two tendencies reduce each other’s impact, providing acceptable robustness.


Author(s):  
G. Resconi

Any problem-solving can be modelled by actions or methods by which from resources or data, one agent makes an action to obtain a result or arrive at a task. A network of actions can be used as a model of the behaviour of the agents. Any sink in the network is a final goal or task. The other tasks are only intermediate tasks. Any source in the network is a primitive resource from which we can begin to obtain results or tasks. Cycles in the network are self-generated resources from the tasks. Now we denote “agent” as the first order that any agent can make one action or can run a method. Now we argue that there also exist agents at the second and at the more high order. Agents that copy the agents of the first order are agents of the second order. To copy one agent of the first order means to copy all the properties of one agent or part of the properties. This is similar to the offspring for animals. The network of resources, action, and tasks in the new agent, has the same properties or part of the properties of the original network. In the copy process, it is possible that the new agent has new properties that are not present in the prototype agent. This is similar to the genetic process of the cross over. The agent of the second order uses the prototype agent as a reference to create new a agent in which all the properties or part of the properties of the original agent are present. When all properties of the prototype network of agents are copied in the new network of agents, we have a symmetry between the prototype network of agents in the new network. When agents are permuted in the same network, agents can change their type of activities without losing the global properties of the network. The properties are invariant for the copy operation as permutation. We remember that also, if two networks of agents have the same properties, they are not equal. When in the copy process, only part of the properties do not change, and new properties appear; in this case we say that we have a break of symmetry. For example, in the animals in the clone process, one cellule is generated from another. The new cell has the same properties of the old cell. In this case, we have symmetry among cells. In fact, because any cell is considered as a network of internal agents (enzymes), two cells are in a symmetric position when the internal network of both the cells have the same properties. With the sexual copy process, it is possible that we lose properties or we generate new properties. In this case, the cellular population assume or lose properties. We break the symmetry in the cellular population. The adaptation process can be considered as a copy process triggered by the environment. For example, to play chess is a network of possible actions with resources and tasks. Any player is an agent of the second order that can change the network of the possible actions. The player can copy the schemes or network of actions located in the external environment in his mind. A physician that makes a model of the nature is a second order agent that makes a copy of the agent’s network of actions in a physical nature into the symbolic domain of the mathematical expressions. Agents as ants can share resources from one field generated by other agents or ants. This field is a global memory that is used by the agents. For example, an ant pheromone field, generated by any ant, is used by all ants. In this way, ants are guided to obtain their task (minimum path). In this case, the pheromone field is an example of global memory resource. The network of connection among ants and its field is shown in the article. Agents that take care to copy one network of agents in another network of agents are agents of the second order. Because we can also copy the network of agents of the second order by agents, these agents are at the third order. In this way, agents of any order can control and adapt a network of agents at a lesser order.


2001 ◽  
Vol 66 (3) ◽  
pp. 1458-1470 ◽  
Author(s):  
A. S. Morozov ◽  
J. K. Truss

AbstractThe relationship between ideals I of Turing degrees and groups of I-recursive automorphisms of the ordering on rationals is studied. We discuss the differences between such groups and the group of all automorphisms, prove that the isomorphism type of such a group completely defines the ideal I, and outline a general correspondence between principal ideals of Turing degrees and the first-order properties of such groups.


1993 ◽  
Vol 58 (1) ◽  
pp. 193-204 ◽  
Author(s):  
Carl G. Jockusch ◽  
Theodore A. Slaman

A first-order sentence Φ is Σ2 if there is a quantifier-free formula Θ such that Φ has the form . The Σ2-theory of a structure for a language ℒ is the set of Σ2-sentences of ℒ true in . It was shown independently by Lerman and Shore (see [Le, Theorem VII.4.4]) that the Σ2-theory of the structure = 〈D, ≤ 〉 is decidable, where D is the set of degrees of unsolvability and ≤ is the standard ordering of D. This result is optimal in the sense that the Σ3-theory of is undecidable, a result due to J. Schmerl. (For a proof, see [Le, Theorem VII.4.5]. As Lerman has pointed out, this proof should be corrected by defining θσ to be ∀xσ1(x) rather than ∀x(ψ(x)→ σ1(x)).) Nonetheless, in this paper we extend the decidability result of Lerman and Shore by showing that the Σ2-theory of is decidable, where ⋃ is the least upper bound operator and 0 is the least degree. Of course ⋃ is definable in , but many interesting degree-theoretic results are expressible as Σ2-sentences in the language of ∪ but not as Σ2-sentences in the language of . For instance, Simpson observed that the Posner-Robinson cupping theorem could be used to show that for any nonzero degrees a, b, there is a degree g such that b ≤ a ⋃ g, and b ⋠ g (see [PR, Corollary 6]). However, the Posner-Robinson technique does not seem to suffice to decide the Σ2-theory of ∪. We introduce instead a new method for coding a set into the join of two other sets and use it to decide this theory.


1982 ◽  
Vol 47 (1) ◽  
pp. 8-16 ◽  
Author(s):  
Richard A. Shore

Relativization—the principle that says one can carry over proofs and theorems about partial recursive functions and Turing degrees to functions partial recursive in any given set A and the Turing degrees of sets in which A is recursive—is a pervasive phenomenon in recursion theory. It led H. Rogers, Jr. [15] to ask if, for every degree d, (≥ d), the partial ordering of Turing degrees above d, is isomorphic to all the degrees . We showed in Shore [17] that this homogeneity conjecture is false. More specifically we proved that if, for some n, the degree of Kleene's (the complete set) is recursive in d(n) then ≇ (≤ d). The key ingredient of the proof was a new version of a result from Nerode and Shore [13] (hereafter NS I) that any isomorphism φ: → (≥ d) must be the identity on some cone, i.e., there is an a called the base of the cone such that b ≥ a ⇒ φ(b) = b. This result was combined with information about minimal covers from Jockusch and Soare [8] and Harrington and Kechris [3] to derive a contradiction from the existence of such an isomorphism if deg() ≤ d(n).


1991 ◽  
Vol 56 (2) ◽  
pp. 563-591 ◽  
Author(s):  
Peter G. Hinman ◽  
Theodore A. Slaman

Since its introduction in [K1-Po], the upper semilattice of Turing degrees has been an object of fascination to practitioners of the recursion-theoretic art. Starting from relatively simple concepts and definitions, it has turned out to be a structure of enormous complexity and richness. This paper is a contribution to the ongoing study of this structure.Much of the work on Turing degrees may be formulated in terms of the embeddability of certain first-order structures in a structure whose universe is some set of degrees and whose relations, functions, and constants are natural degree-theoretic ones. Thus, for example, we know that if {P, ≤P) is a partial ordering of cardinality at most ℵ1 which is locally countable—each point has at most countably many predecessors—then there is an embeddingwhere D is the set of all Turing degrees and <T is Turing reducibility. If (P, ≤P) is a countable partial ordering, then the image of the embedding may be taken to be a subset of R, the set of recursively enumerable degrees. Without attempting to make the notion completely precise, we shall call embeddings of the first sort global, in contrast to local embeddings which impose some restrictions on the image set.


2009 ◽  
Vol 78 (4) ◽  
pp. 1189-1198
Author(s):  
Uri Andrews ◽  
Julia F. Knight

AbstractFor a countable structure , the spectrum is the set of Turing degrees of isomorphic copies of . For a complete elementary first order theory T, the spectrum is the set of Turing degrees of models of T. We answer a question from [1] by showing that there is an atomic theory T whose spectrum does not match the spectrum of any structure.


1982 ◽  
Vol 47 (3) ◽  
pp. 587-604 ◽  
Author(s):  
Julia Knight ◽  
Mark Nadel

If is a countable recursively saturated structure and T is a recursively axiomatizable theory that is consistent with Th(), then it is well known that can be expanded to a recursively saturated model of T [7, p. 186]. This is what has made recursively saturated models useful in model theory. Recursive saturation is the weakest notion of saturation for which this expandability result holds. In fact, if is a countable model of Pr = Th(ω, +), then can be expanded to a model of first order Peano arithmetic P just in case is recursively saturated (see [3]).In this paper we investigate two natural sets of Turing degrees that tell a good deal about the expandability of a given structure. If is a recursively saturated structure, I() consists of the degrees of sets that are recursive in complete types realized in . The second set of degrees, D(), consists of the degrees of sets S such that is recursive in S-saturated. In general, I() ⊆ D(). Moreover, I() is obviously an “ideal” of degrees. For countable structures , D() is “closed” in the following sense: For any class C ⊆ 2ω, if C is co-r.e. in S for some set S such that , then there is some σ ∈ C such that . For uncountable structures , we do not know whether D() must be closed.


2019 ◽  
Vol 42 ◽  
Author(s):  
Daniel J. Povinelli ◽  
Gabrielle C. Glorioso ◽  
Shannon L. Kuznar ◽  
Mateja Pavlic

Abstract Hoerl and McCormack demonstrate that although animals possess a sophisticated temporal updating system, there is no evidence that they also possess a temporal reasoning system. This important case study is directly related to the broader claim that although animals are manifestly capable of first-order (perceptually-based) relational reasoning, they lack the capacity for higher-order, role-based relational reasoning. We argue this distinction applies to all domains of cognition.


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